PhD Roxane Autissier
email: roxane.autissier@uca.fr

Leslie Mazuel

Elise Maubert

Jean-Marie Bonny

Philippe Auzeloux

Sébastien Schmitt

Amidou Traoré

Caroline Peyrode

Elisabeth Miot-Noirault

Guilhem Pagès

; Leslie Mazuel

Simultaneous proteoglycans and hypoxia mapping of chondrosarcoma environment by frequency selective CEST MRI

Keywords: Simultaneous proteoglycans and hypoxia mapping CEST, Chondrosarcoma, Hypoxia, MRI, Nuclear imaging, Proteoglycans

de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

INTRODUCTION

Chondrosarcoma (CHS) is a malignant cartilaginous tumor representing the most common primary bone cancer in adults. [START_REF]Key Statistics for Bone Cancer: Key Statistics About Bone Cancer[END_REF][START_REF] Health Organization | WHO Classification of Tumours of Soft Tissue and Bone[END_REF] CHS is characterized by a dense heterogeneous extracellular matrix (ECM), a low percentage of dividing cells and poor vascularity. [START_REF] Gelderblom | The clinical approach towards chondrosarcoma[END_REF] The combination of these three factors leads to chemo and radiation therapy resistance. [START_REF] Mery | Biological aspects of chondrosarcoma: Leaps and hurdles[END_REF][START_REF] Angelini | Clinical outcome of central conventional chondrosarcoma[END_REF][START_REF] Van Oosterwijk | Update on targets and novel treatment options for high-grade osteosarcoma and chondrosarcoma[END_REF][START_REF] Nazeri | Chondrosarcoma: An overview of clinical behavior, molecular mechanisms mediated drug resistance and potential therapeutic targets[END_REF][START_REF] Yeldag | Chemoresistance and the self-maintaining tumor microenvironment[END_REF] Dense and fibrotic ECM with high levels of collagen and proteoglycans (PGs) is recognized to impair interstitial transport of drug from blood to cancer cells. [START_REF] Davies C De | Comparison of IgG diffusion and extracellular matrix composition in rhabdomyosarcomas grown in mice versus in vitro as spheroids reveals the role of host stromal cells[END_REF] In addition, the acidic microenvironment associated with hypoxia may electrostatically charge the drugs, limiting their ability to cross biological membranes. [START_REF] Trédan | Drug resistance and the solid tumor microenvironment[END_REF] In vivo assessment of the phenotypic topological heterogeneity of the tumor microenvironment is key to optimizing personalized therapies. Although, biopsy is subject to sampling and pathologist/observer variability, microenvironmental characterization is mainly achieved from biopsy samples to determine grade and staging of the disease. [START_REF]Skeletal Lesions Interobserver Correlation among Expert Diagnosticians (SLICED) Study Group. Reliability of histopathologic and radiologic grading of cartilaginous neoplasms in long bones[END_REF] Tumor evaluation requires access to morphological and protein information in a context that takes into account intratumoral heterogeneity as a whole. In such a situation, developing imaging methods to access the main recognized CHS features, i.e. chondrogenic matrix and hypoxia, would be of great interest for diagnosis and clinical follow-up. Indeed, the current clinical imaging methods recommended, i.e. CT and MRI, [START_REF] Murphey | From the archives of the AFIP: imaging of primary chondrosarcoma: radiologic-pathologic correlation[END_REF] are used to define tumor morphology and distinguish postoperative residues from postoperative or post-chemotherapeutic residual lesions. However, such approaches cannot be used in the same manner as functional imaging to assess tumor environment. [START_REF] Logie | Chondrosarcoma: A diagnostic imager's guide to decision making and patient management[END_REF] Functional imaging can be done with specific radiotracers to access metabolic data useful to diagnose and assess the therapeutic response of CHS. Due to their rarity, there is a lack of large trials on functional imaging of chondroid tumors. Nowadays, nuclear medicine used to image CHS in a clinical context targets either the bone remodeling or the glucose tumoral metabolism with radiotracers such as 99m Tc-MDP or [START_REF] Rajendran | Hypoxia and glucose metabolism in malignant tumors: Evaluation by [18F]Fluoromisonidazole and [18F]Fluorodeoxyglucose positron emission tomography imaging[END_REF] F-FDG, respectively. [START_REF] Jo | Diagnostic accuracy of functional imaging modalities for chondrosarcoma: A systematic review and meta-analysis[END_REF] To more accurately image the CHS microenvironment, radiotracers should target either ECM PGs or the CHS hypoxia feature. 99m Tc-NTP 15-5 emerged from our lab as a candidate SPECT tracer for the functional imaging of cartilage by targeting PG negative charges in ECM. It demonstrated its relevance to specifically diagnose on CHS animal model and is expected to enter clinical trials shortly. [START_REF] Miot-Noirault | First preclinical imaging of primary cartilage neoplasm and its local recurrence using 99mTc-NTP 15-5 radiotracer[END_REF][START_REF] Peyrode | Proteoglycan targeting strategy" for the scintigraphic imaging and monitoring of the swarm rat chondrosarcoma orthotopic model[END_REF][START_REF] Miot-Noirault | In vivo scintigraphic imaging of proteoglycans[END_REF] One of the radiotracers extensively used in clinic for hypoxia is 18 F-FMISO. [START_REF] Rajendran | Hypoxia and glucose metabolism in malignant tumors: Evaluation by [18F]Fluoromisonidazole and [18F]Fluorodeoxyglucose positron emission tomography imaging[END_REF] As with many nitroimidazole derivatives, under reduced oxygen conditions, this tracer is reduced into a R-NO 2 radical that binds covalently to intracellular molecules leading ultimately to the entrapment of the tracer in hypoxic cells. To image both tumor features, two nuclear exams are required with two injections of radioactive contrast agent. Therefore, it would be interesting to develop a method to simultaneously image both of the metabolic properties of CHS.

The recent rise of CEST MRI has opened up new perspectives in the imaging of biological molecules within the tumoral microenvironment. [START_REF] Goldenberg | Assessments of tumor metabolism with CEST MRI[END_REF] This method is based on the exchange between saturated labile protons of the solute with the bulk water, revealing the endogenous contrast of some chemical functions. CEST MRI indirectly maps these low concentration metabolites by monitoring the variation of an elevated water signal. Typically, a CEST experiment is a 2-step process. First, the magnetic field inhomogeneity has to be mapped; this is the function of the so-called water saturation shift referencing (WASSR) acquisition. Second, MR images must be recorded at several saturation frequency offsets to record a z-spectrum (normalized water signal as a function of the saturation offset for each voxel). This z-spectrum, with a zero-frequency referenced to the water's frequency will display an extra water attenuation at the metabolite exchangeable proton frequency, i.e. the CEST effect. To quantify this CEST effect, the first proposed method was based on the analysis of the water signal intensity at the offset of interest and its counterpart negative value. This magnetization transfer ratio asymmetry (MTRasym) analysis hypothesizes the absence of the magnetization transfer effect for negative offsets. As this hypotheses is not systematically verified, other z-spectrum analyses were developed, i.e. a threeoffset measurement approach or multiple-pool Lorentzian fitting method. [START_REF] Jin | MR imaging of the Amide-Proton Transfer effect and the pHinsensitive Nuclear Overhauser Effect at 9.4 T[END_REF][START_REF] Zhou | Magnetic resonance imaging of glycogen using its magnetic coupling with water[END_REF] Hydroxyl, guanidyl and amide moieties were independently imaged by CEST MRI. [START_REF] Jones | Clinical applications of chemical exchange saturation transfer (CEST) MRI[END_REF][START_REF] Kogan | Chemical Exchange Saturation Transfer (CEST) imaging: Description of technique and potential clinical applications[END_REF] Readers interested in a deeper explanation of CEST MRI principles are referred to the following references. [START_REF] Van Zijl | Chemical Exchange Saturation Transfer (CEST): what is in a name and what isn't?[END_REF][START_REF] Wu | An overview of CEST MRI for non-MR physicists[END_REF][START_REF] Dou | Chemical exchange saturation transfer magnetic resonance imaging and its main and potential applications in pre-clinical and clinical studies[END_REF] CEST MRI has demonstrated its relevance for the quantitative evaluation and mapping of PGs in cartilaginous tissues by assessing the chemical exchange of saturable protons with the hydroxyl groups (i.e., around 0.5 -1.5 ppm) of GAG molecules [START_REF] Ling | Assessment of glycosaminoglycan concentration in vivo by chemical exchange-dependent saturation transfer (gagCEST)[END_REF][START_REF] Brinkhof | Detection of early cartilage damage: feasibility and potential of gagCEST imaging at 7T[END_REF] in both physiological and pathological situations. (29- 31) In addition, CEST MRI has been demonstrated to be sensitive to pH variations, indirectly revealing information on the metabolic switch in response to hypoxia. [START_REF] Corbet | Tumour acidosis: from the passenger to the driver's seat[END_REF] Several studies have demonstrated that pH variations impact the chemical exchange rate of both guanidyl and amide moieties. [START_REF] Chen | Evaluating pH in the extracellular tumor microenvironment using CEST MRI and other imaging methods[END_REF][START_REF] Jin | Enhancing sensitivity of pH-weighted MRI with combination of amide and guanidyl CEST[END_REF] The change in the chemical exchange rate with the pH leads to a variation of the CEST intensity at frequencies of around 1.8 -2.4 and 3.0 -4.0 ppm for guanidyl and amide proton transfer (APT) CEST, respectively. Therefore, the combination of both guanidyl and APT CEST has been proposed as a highly sensitive method to explore extracellular pH acidification in tumors. [START_REF] Maloney | Magnetic resonance imaging biomarkers for pulsed focused ultrasound treatment of pancreatic ductal adenocarcinoma[END_REF][START_REF] Loi | Relaxation-compensated CEST (chemical exchange saturation transfer) imaging in breast cancer diagnostics at 7T[END_REF] Considering that PGs and pH each have their own resonance frequencies, and are therefore sensitive to different exchangeable moieties, we decided these two features would merit further study using a single CEST MRI acquisition on CHS animal model. The aim of this study was to evaluate the relevance of frequency-selected CEST MRI to simultaneously map PG concentration and pH of CHS tissue in vivo. To validate this approach, CEST MRI was compared to the standard reference nuclear imaging as well as ex vivo analysis.

METHODS

GAG and pH phantom experiments

Phosphate-buffered saline (PBS) 1X (Gibco Laboratories, Gaithersburg, MD, USA) containing 1% of bovine serum albumin (BSA) solution (Sigma Aldrich, St. Louis, MO, USA) was used to prepare the chondroitin 4-sulfate phantom. Five samples of the chondroitin 4-sulfate (Sigma Aldrich, St. Louis, MO, USA) were prepared at. 1; 5; 10; 20; 40 mg/mL at pH 7.4. For protamine phantom, 15 mg/mL of protamine (Sigma Aldrich, St. Louis, MO, USA) and 0.15 mM of MnCl 2 were dissolved in PBS. Four samples of protamine were prepared with pH ranging from 6.5 to 7.7 in 0.4 unit increments. Both phantoms (chondroitin 4-sulfate and protamine) were prepared with 15 % gelatin in water to fix the syringes containing the different solutions. Phantoms were submitted to the same acquisition and analysis protocols as described below except for B 1 , which was set to 3 µT.

2.2. Xenograft model of SWARM rat CHS Experiments were conducted in accordance with the European directive 2010/63/EU after approval by the animal ethical committee C2E2A, authorization number: #15991.

SWARM rat CHS (SRC) xenografts were performed in 5 week old female NMRI Nude immunodeficient mice (Janvier Labs, Le Genest-Saint-Isle, FR) from frozen fragments after reactivation in 4 week old male Sprague Dawley rats (Charles River Laboratories France, Saint Germain Nuelles, FR). For reactivation, SRC fragments were defrosted in Dulbecco's Modified Eagle Medium (DMEM, Gibco Laboratories, Gaithersburg, MD, USA) then implanted subcutaneously on the right flank of 3 anesthetized rats (isoflurane; 2.5 %, 1 L/min, air/O 2 , 70/30, v/v). After 22 days post-surgery, tumors were resected and immediately placed in cold DMEM. Then, they were manually calibrated to 1 mm 3 and transplanted subcutaneously between the shoulder blades on anesthetized (isoflurane; 1.5 %, 1 L/min, air/O 2 , 70/30, v/v) NMRI Nude immunodeficient mice (n=10) and cutaneous wounds were sutured.

In vivo animal imaging

All imaging experiments were performed at "In Vivo Imaging in Auvergne" (IVIA) facility (https://doi.org/10.18145/ivia). Imaging protocols were performed on the same mice between 12 and 16 days after induction, corresponding to an average tumoral volume of 215.04 ± 86.28 mm 3 (see supporting Figure S1). During these in vivo acquisitions, all animals were anesthetized by isoflurane (1.5 %, 1 L/min, air/O 2 , 70/30, v/v). All animals were secured on a dedicated bed with both breathing rate and temperature being monitored during acquisitions. Supporting Table S1 describes in details the animal distribution for each imaging modality.

2.3.1.MR imaging

MR images of mice (n = 10) were acquired on an 11.7 Tesla Bruker BioSpec system (Bruker BioSpin, Ettlingen, Germany) piloted by Paravision 6.0.1 software. A 72 mm circular polarizer volume coil was used for RF transmission and a surface array coil (2x2) positioned on both the tumor and the adjacent muscle received the NMR signal (Bruker BioSpin, Ettlingen, Germany).

DW imaging: Tumor imaging was performed with a DWI sequence (b=500 s.mm -2 , direction [0,0,1]) with a TE of 27 ms and a TR of 2000 ms. The FOV was 40 mm with an axial slice thickness of 1 mm leading to a nominal resolution of 0.26 × 0.26 × 1 mm 3 . The number of slices was adjusted to image the whole tumor (generally, 12 slices were needed). Two averages were performed for a total acquisition time of 7 min 32 s.

CEST Imaging: CEST acquisitions were based on a RARE sequence with an effective TE and TR of 4.756 and 4500 ms, respectively and a RARE acceleration factor of 16. The slice thickness was 2 mm and the FOV 40 mm, i.e. the in-plane voxel size was 0.625 × 0.625 mm². Each image was recorded from a single transient. A first z-spectrum was recorded to correct for B 0 inhomogeneities by using the WASSR approach [START_REF] Kim | Water saturation shift referencing (WASSR) for chemical exchange saturation transfer (CEST) experiments[END_REF] (saturation pulses B 1 0.1 54.8 ms gaussian pulses repeated 18 times with an interpulse delay of a 0.010 ms, and a bandwidth of 20 Hz leading to a train of 1 s; saturation offsets from ± 1000 Hz with 20 Hz) followed by the CEST z-spectrum (30 min acquisition duration with saturation pulses: B 1 1. 5 54.8 ms gaussian pulses repeated 72 times with a bandwidth of 50 Hz leading to a train of 4 s and an equivalent continuous wave CEST saturation of 0.6 µT; saturation offsets from ± 2500 Hz with 50 Hz). CEST MRI data were analyzed with an in-house program written in MATLAB ® R2017a (MathWorks, Natick, MA USA). In brief, a ROI was manually drawn on the highresolution DW image to delineate the tumor and muscle of the scapular region. Then, B 0 shift was corrected pixel-by-pixel with the WASSR approach. Finally, the CEST methodology applied to analyze the data depended on the saturation offset. For GAG CEST, the analysis was performed on the whole image and the z-spectrum was fitted with two Lorentzian shapes: the first one to estimate the signal attenuation due to the water direct saturation (centered at 0 ppm) and the second one for the hydroxyl moieties. The GAG CEST signal intensity corresponded to the area of this latter Lorentzian shape. Regarding guanidyl and APT CEST, we applied the three-offset measurement approach proposed by Jin et al. [START_REF] Jin | MR imaging of the Amide-Proton Transfer effect and the pHinsensitive Nuclear Overhauser Effect at 9.4 T[END_REF] to avoid nuclear overhauser enhancement (NOE) interferences. In practice, two limits were chosen (1.60 to 2.40 and 3.20 to 4.00 ppm for the guanidyl and amide moieties, respectively) and a baseline was drawn between these frequencies. The CEST effect for APT* and guanidyl* were quantified as the difference between the baseline and the water signal at 1.96 and 3.68 ppm, respectively. The ratio of APT*/guanidyl* was then calculated. The relative variation of this ratio was expressed from the mean ratio value on the ROI.

2.3.2.Nuclear Imaging

PGs imaging by SPECT/CT using 99m Tc-NTP 15-5 radiotracer: SPECT-CT images were acquired using a camera (NanoScan ® ,Mediso Ltd, Budapest, Hungary) equipped with four multi pinhole detectors APT62. Acquisitions were performed on Nucline software (v3.00.018, Mediso Ltd, Budapest, Hungary). 20 MBq of 99m Tc-NTP 15-5, radiolabeled as described [START_REF] Vidal | Development of a freeze-dried kit formulation for the preparation of 99m Tc-NTP 15-5, a radiotracer for scintigraphic imaging of proteoglycans[END_REF] , were injected intravenously in the tail vein. After 30 min, mice (n = 10) were anesthetized and imaged. Anatomic CT acquisition consisted of a helical scan with 480 projections, 300 ms per projection, 50 kV, 590 µA. Then, SPECT images were performed with 128 projections, 20 s per projection and an energy window set at 140 keV ± 20 %. After image reconstructions using the 3D ordered subset expectation maximization (3D OSEM) algorithm, analyses were performed with Interview TM FUSION (v3.03.074, Mediso Ltd, Budapest, Hungary) software using an interpolated ellipse ROI for both tumor and scapular muscle manually drawn slice by slice. Activity concentrations were obtained in kBq/mL.

Hypoxia PET imaging using [START_REF] Rajendran | Hypoxia and glucose metabolism in malignant tumors: Evaluation by [18F]Fluoromisonidazole and [18F]Fluorodeoxyglucose positron emission tomography imaging[END_REF] F-FMISO: PET images were acquired using a small animal device (eXplore Vista ® , GE Healthcare, Chicago, IL, USA). 30 MBq of [START_REF] Rajendran | Hypoxia and glucose metabolism in malignant tumors: Evaluation by [18F]Fluoromisonidazole and [18F]Fluorodeoxyglucose positron emission tomography imaging[END_REF] F-FMISO were injected intravenously in the tail vein. Four hours later, the mice (n = 10) were anesthetized and PET imaging was performed with a 250 to 700 keV energy window and 6 ns coincidence time window (30 min duration, 2 bed positions) with MMWKS ® Image software (GE Healthcare, Chicago, IL, USA). After 2D OSEM reconstructions, analyses were performed with VivoQuant TM (v4.0 patch1, inviCRO, Boston, MA, USA) software using a 3D ROI for tumor and scapular muscle manually drawn. [START_REF] Rajendran | Hypoxia and glucose metabolism in malignant tumors: Evaluation by [18F]Fluoromisonidazole and [18F]Fluorodeoxyglucose positron emission tomography imaging[END_REF] F-FMISO uptake was quantified in kBq/mL.

Ex vivo analysis

Histological and immunofluorescence analysis in tumoral tissues were performed at the histopathology facility ANIPATH (CNRS UMR 6293 / Inserm U1103 GReD, Clermont-Ferrand, FR).

After a multimodal imaging session, 20 days post-induction, mice (n = 3) were sacrificed by cervical dislocation under anesthesia and tumors were resected and cut into two samples. The first sample was fixed into 10 % neutral buffered formalin for 24 h and embedded in paraffin for histological analysis (alcian blue or pimonidazole staining). The second sample was frozen in liquid nitrogen for GAG assays. For pimonidazole analysis, animals received an intraperitoneal injection of pimonidazole hydrochloride (60 mg/kg, Hypoxyprobe TM , Burlington, MA, USA) 1 hour before sacrifice.

Alcian blue staining: 5 µm thick sections of embedded tumors were cut and adhered to poly-L-Lysine-coated microscope slides. After dewaxing and rehydration, slides were stained by Alcian blue (pH 1) to visualize PGs, counterstained by nuclear red after which coverslips were fixed. Staining was detected and images were recorded using a slide scanner (X20, Zeiss AxioScan Z1, ZEN software).

Pimonidazole staining: 5 µm thick sections of embedded tumors were cut and adhered to poly-L-Lysine-coated microscope slides. After dewaxing and rehydration of tumor slices, antigens were retrieved (boiling tris: 10 mM, pH 6) and slides were placed into the InsituPro VSi robot (Intavis bioanalytical instruments, Köln, Germany). Endogenous peroxidases were quenched (H 2 O 2 : 0.3 %, 30 min) and saturated (BSA: 1 %, 1 h). Slides were then incubated with a primary antibody (antipimonidazole: mouse monoclonal antibody, 1/300, 1h, RT; Hypoxyprobe TM ). Biotinylated secondary antibody (1/500, BSA 0.1 %, 1 h; Vector Laboratories) was used to reveal the first antibody. Biotin was then complexed with streptavidin-coupled horseradish peroxidase (HRP) (1/500, 30 min; Vector Laboratories). Peroxidase was detected using tyramide signal amplification (TSA) as per manufacturer's instructions (TSA-Alexa488; Invitrogen TM ). Then, nuclei were counterstained with Hoechst (33342) and coverslips were fixed. Emitted fluorescences (461 nm for Hoechst and 519 nm for TSA) were imaged and recorded as previously (X20, Zeiss AxioScan Z1, ZEN software, Oberkochen, Germany). GAG assay: samples (n=10) were weighed (20-50 mg) and incubated overnight at 65°C in 1 mL of a papain extraction buffer and then centrifuged (1000 g, 10 min). Sulfated GAG content was determined using a Blyscan® Sulfated Glycosaminoglycan assay kit (Biocolor Ltd, Carrickfergus, UK) as per manufacturer's instructions. Absorbance was measured at 656 nm using Thermo Scientific Multiskan GO device (Thermo Fisher Scientific, Waltham, MA, USA). Experiments were performed in duplicates.

Statistical analyses

Statistical analyses were performed on Prism software version 6.0 (GraphPad Software, San Diego, CA, USA). For in vivo and ex vivo studies, data were presented as individual values with mean ± SD. Data normal distributions were verified with Shapiro-Wilk tests before performing Student's t-tests. For in vivo imaging quantification, paired Student's t-tests were applied and for ex vivo analyses, unpaired Student's t-tests were performed. Results were considered significant at P < 0.05 (*P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001). Significance of results was verified with a Wilcoxon matchedpairs signed rank test.

RESULTS

3.1. GAG, guanidyl and APT CEST on phantoms GAG CEST effects were observed on the z-spectra of chondroitin 4-sulfate solutions (Figure 1A) and guanidyl and APT CEST effects on that of protamine solutions (Figure 1C). The highest CEST effect offset for each moiety appeared at different chemical shifts: 0.75, 1.96 and 3.68 ppm for GAGs, guanidyl and APT, respectively.

Linear relationships were found between CEST AUCs and either the GAG concentration (R 2 =0.9845) or the pH (R 2 =0.8849 and R 2 =0.8477, for Guanidyl* and APT* respectively). An increase in GAG concentration and in pH led to an increase of the CEST signal (Figure 1B,1D). The relative variation of the ratio (reference pH at 7.2) increased from pH 6.8 to 7.7.

***Figure 1 appears near here*** 3.2. Quantitative assessment of GAGs in CHS tumoral tissue From signal analysis of GAGs by CEST MRI, a GAG concentration-related map (Figure 2A) was constructed. The signal from GAG was clearly evidenced within tumoral tissue, and was observed to be heterogeneously distributed. Regarding muscle, CEST MRI of GAGs was very low with AUC =2.15 ± 1.88 as compared to 27.29 ± 8.38 in tumor (P < 0.0001; n=9) (Figure 2B) leading to a tumor/muscle ratio of 23.35 ± 16.97 Nuclear imaging, evidenced a significantly (P < 0.0001; n=9) higher uptake of the 99m Tc-NTP 15-5 radiotracer in tumoral tissue (179.38 ± 38.39 kBq/mL) as opposed to muscle (35.07 ± 5.17 kBq/mL), leading to a tumor/muscle ratio of 5.11 ± 0.69 (Figure 2C and2D). Four images of 99m Tc-NTP 15-5 SPECT imaging are shown on supporting Figure S3A. Ex vivo experiments confirmed this high PG feature of CHS tissue. From biochemical assays, GAG concentration was demonstrated to be 6.33 ± 1.60 µg/mg in the tumor while it was only 0.41 ± 0.09 µg/mg in the muscle (P < 0.0001) (Figure 2F). As illustrated on figure 2E, tumoral tissue was strongly stained by alcian blue confirming its richness in GAGs.

***Figure 2 appears near here*** 3.3. Quantitative assessment of pH and hypoxia in CHS tumoral tissue Figures 3A shows both the anatomical and relative variation of the APT*/guanidyl* ratio images for 3 randomly chosen mice out of 7. The ratio was only calculated inside the tumor as it cannot be compared with muscle due to extra CEST signal coming from creatine and phosphocreatine. The CESTbased images highlighted a heterogeneous pH distribution inside the tumor.

Figure 3B displays a representative image of 18 F-FMISO PET. While on this slice, a clear difference between the tumor and the muscle was observed, this was no longer the case once the signal was integrated over the whole tumor (red dots on Figure 3C). At the group level (n=5), the tumor mean signal (18.70 ± 10.54 kBq/mL) was different from the muscle's signal (8.60 ± 4.30 kBq/mL). However, the inter-individual variations, especially for the tumor, led to the absence of differences between both tissues. The three incidences of [START_REF] Rajendran | Hypoxia and glucose metabolism in malignant tumors: Evaluation by [18F]Fluoromisonidazole and [18F]Fluorodeoxyglucose positron emission tomography imaging[END_REF] F-FMISO PET imaging are shown on supporting Figure S3B.

Ex vivo experiments by immunofluorescence with pimonidazole evidenced a weak staining within tumoral tissue, mainly localized in the center of CHS lobules (Figure 3D). ***Figure 3 appears near here*** 4. DISCUSSION This work aimed to develop in one-scan multiple CEST MRI contrasts to characterize in vivo PG and hypoxic features of the CHS microenvironment. By exploiting the CEST frequency selectivity, we aimed to simultaneously image the PG concentration and pH as it relates to hypoxia. CEST MRI images were compared to current state of the art imaging approaches, i.e. 99m Tc-NTP 15-5 and 18 F-FMISO to map PGs and hypoxia, respectively. To our knowledge, this work is the first one to investigate the microenvironment of CHS by CEST MRI. In most published studies exploiting CEST MRI to image GAG concentration and pH, different saturation protocols are used. Both level and duration of the saturation RF trains are optimized depending on the exchangeable protons targeted. Typically, to image the hydroxyl moieties, the saturation pulse level is moderate while the duration is long. [START_REF] Zhou | Quantitative chemical exchange saturation transfer MRI of intervertebral disc in a porcine model[END_REF][START_REF] Nasrallah | Imaging brain deoxyglucose uptake and metabolism by glucoCEST MRI[END_REF] For APT CEST, a variety of saturation conditions have been used. [START_REF] Zhou | APT-Weighted MRI: techniques, current neuro applications, and challenging issues[END_REF] However, to maximize the APT effect, Zhou et al. [START_REF] Zhou | APT-Weighted MRI: techniques, current neuro applications, and challenging issues[END_REF] recommend the usage of a saturation duration higher than 0.8 s and a level of around 2 µT. Our experimental conditions were close to the optimal ones for the different contrasts. As we wanted to image both tumor features in a single acquisition, we chose to use a long saturation train (t sat =4 s) with moderate power (B 1 =1. 5 that was demonstrated from phantom experiments to be a satisfactory compromise. Indeed, the GAG CEST effect was not too broad and did not overlap with the guanidyl one. Obviously, this compromise on the saturation parameters is at the cost of the optimized sensitivity for each CEST effect. Carefully choosing the saturation frequencies made it possible to simultaneously assess PGs (GAG CEST) and pH (guanidyl and APT CEST). In vitro, we can note that we found an increase of the guanidyl* signal like Oskolkov et al. [START_REF] Oskolkov | Biophysical characterization of human protamine-1 as a responsive CEST MR Contrast Agent[END_REF] while Jin et al. [START_REF] Jin | Enhancing sensitivity of pH-weighted MRI with combination of amide and guanidyl CEST[END_REF] observed an opposite trend. This discrepancy can be due to (i) our multiple-contrast CEST conditions, experimental conditions were not set to the optimal values to maximize the CEST effect for pH, (ii) physical parameters, especially the chemical exchange rate constant, are not comparable to what was simulated in the other study. To obtain a pH variation independent of protein concentration, the ratio of the APT* and guanidyl* CEST was calculated.

In vivo GAG CEST images were obtained by acquiring signals resulting from the chemical exchange of the abundant hydroxyl groups in GAGs. A 23 times higher CEST effect was observed for the tumor compared to muscle demonstrating the high PG density in the CHS microenvironment. CEST signal studies of different forms of GAGs typically found in articular cartilage recently demonstrated that the CEST effect arises mainly from chondroitin 4-sulfate. [START_REF] Einarsson | The role of cartilage glycosaminoglycan structure in gagCEST[END_REF] SRC was demonstrated to highly express aggrecan which is composed of a core protein with covalently attached side chains of linear GAGs, including a high number of chondroitin sulfate, especially chondroitin 4-sulfate. [START_REF] Choi | Mucopolysaccharide and protein-polysaccharide of a transplantable rat chondrosarcoma[END_REF] The GAG CEST approach was combined with 99m Tc-NTP 15-5 nuclear imaging, a radiotracer designed to target negatively charged molecules of GAGs. [START_REF] Peyrode | Proteoglycan targeting strategy" for the scintigraphic imaging and monitoring of the swarm rat chondrosarcoma orthotopic model[END_REF][START_REF] Miot-Noirault | First preclinical imaging of primary cartilage neoplasm and its local recurrence using 99mTc-NTP 15-5 radiotracer[END_REF] As expected, a higher radiotracer accumulation was observed in tumor in respect to muscle (ratio ~5), confirming the higher PG concentration measured by GAG CEST. The discrepancies in the tumor to muscle ratios between the MRI and nuclear imaging can be explained by the poor vascularization of the tumor, thereby limiting the delivery of the radiotracer. Since CEST MRI provided signals from hydroxyl moieties of PGs, we also have to consider that hydroxyl moieties are found in other molecules such as glucose or lactate. [START_REF] Walker-Samuel | In vivo imaging of glucose uptake and metabolism in tumors[END_REF][START_REF] Debrosse | Lactate Chemical Exchange Saturation Transfer (LATEST) Imaging in vivo A Biomarker for LDH Activity[END_REF] We therefore were interested to complete GAG CEST with 1 H MRS to identify their respective contribution in the CEST signal. Unfortunately, due to its high chondrogenic structure, CHS tissue did not provide enough resolution on the MRS spectrum. Finally, ex vivo quantitative analysis, i.e. GAG assays, reinforced the in vivo multimodal imaging results and evidenced high PG concentration within tumoral tissue (ratio tumor/muscle ~18, i.e. in between SPECT and CEST ratios).

CEST MRI assessment of intratumoral pH variations was performed by exploiting both guanidyl and amide to enhance the sensitivity of pH weighted MRI. [START_REF] Jin | Enhancing sensitivity of pH-weighted MRI with combination of amide and guanidyl CEST[END_REF] As acidosis is associated to hypoxia [START_REF] Chiche | Tumour hypoxia induces a metabolic shift causing acidosis: a common feature in cancer[END_REF] , it was expected that mapping tumoral pH through CEST MRI would be a relevant methodology to delineate areas of hypoxic and well oxygenated cells within tumoral tissue. The CEST signals from both chemical groups were assigned to proteins. To have a map independent from protein concentration, the APT*/guanidyl* ratio was calculated inside the tumor. This approach assumes that the guanidyl signal is coming only from the proteins. This hypothesis is acceptable for tumors, although it cannot be applied to other tissues, especially muscle, due to the presence of creatine and phosphocreatine. These metabolites give a guanidyl signal, the APT*/guanidyl* ratio will depend on both pH and the metabolite concentrations. In vivo [START_REF] Rajendran | Hypoxia and glucose metabolism in malignant tumors: Evaluation by [18F]Fluoromisonidazole and [18F]Fluorodeoxyglucose positron emission tomography imaging[END_REF] F-FMISO PET imaging confirmed the hypoxic status of CHS since the mean tumor/muscle ratio value was approximately 2. However, at the group level there was no statistical difference between the two tissues due to large inter-individual variations. Ex vivo immunofluorescence with pimonidazole evidenced that hypoxic areas were heterogeneously distributed throughout the tumoral tissue similarly to CEST MRI.

The assessment of pH by APT CEST is debated in the literature. Some authors reported a decrease of the CEST effect on the pH [START_REF] Schüre | The pH sensitivity of APT-CEST using phosphorus spectroscopy as a reference method[END_REF][START_REF] Wang | Mapping tissue pH in an experimental model of acute stroke -Determination of graded regional tissue pH changes with non-invasive quantitative amide proton transfer MRI[END_REF] while others observed the opposite. [START_REF] Krikken | Contradiction between amide CEST signal and pH in breast cancer explained with metabolic MRI[END_REF][START_REF] Schmidt | Systematic evaluation of amide proton Chemical Exchange Saturation Transfer at 3 T: Effects of protein concentration, pH, and acquisition parameters[END_REF] Most of these APT CEST effects were obtained after performing the so-called MTR asym analysis. The key assumption in this data processing is that for negative offsets, only the direct water saturation effect is recorded. [START_REF] Liu | Nuts and bolts of chemical exchange saturation transfer MRI[END_REF] However, it was shown in vivo that several NOE exchanges were recorded in the region of ~-1 to -4 ppm, no longer fulfilling the MTR asym assumption. [START_REF] Zhang | Accuracy in the quantification of chemical exchange saturation transfer (CEST) and relayed nuclear Overhauser enhancement (rNOE) saturation transfer effects[END_REF] Nevertheless, most of these studies used this estimator. To avoid the interference of the NOE on our CEST quantifications, our data were analyzed by using the approach inspired by Jin et al. [START_REF] Jin | MR imaging of the Amide-Proton Transfer effect and the pHinsensitive Nuclear Overhauser Effect at 9.4 T[END_REF] and described in section 2.3.1.

To conclude, our work on SRC bearing mice demonstrated the potential of imaging the different tumoral microenvironment properties by a single CEST MRI acquisition. MRI presents the main advantage when compared to nuclear imaging to give high-resolution spatial information. It is then possible to delineate accurately the metabolism-related region of interest. Such parametric maps would allow a better understanding of the relationship between tumor cells and their environment, thus becoming a prerequisite to develop more individualized therapies. FIGURE CAPTIONS FIGURE 1: z-spectra of (A) chondroitin 4-sulfate and (C) protamine at several concentrations and pH, respectively. The CEST effects were estimated by measuring the AUC from 0.02 to 1.50 ppm for chondroitin 4-sulfate (GAG CEST) and the signal intensity at 1.96 and 3.60 for guanidyl* and APT* CEST, respectively. The relationship between CEST quantification and concentrations or pH are represented on panels (B) and (D), respectively.

FIGURE 2 :

 2 FIGURE 2: In vivo multimodal imaging of GAGs in SRC bearing mice (A) GAG CEST parametric image. To clearly identify the tumor, the high-resolution image was added inside the inset. (C) SPECT-CT imaging with 99m Tc-NTP 15-5. ROI quantitative analysis of GAG CEST and SPECT-CT are presented in (B) and (D), respectively. (E) Ex vivo tumor slice (X20 magnification) stained with both alcian blue and nuclear red. Data were presented by individual values with mean ± SD. Paired t-test and unpaired t-test (**** P < 0.0001) were applied for in vivo and ex vivo quantifications, respectively. Red data points on panels (B), (D) and (F) correspond to the images shown in (A), (C) and (E), respectively. Abbreviations: T: Tumor; M: muscle.

FIGURE 3 :

 3 FIGURE 3: In vivo multimodal imaging of pH acidification (MRI) and hypoxia (PET) in SRC bearing mice. (A) High resolution and relative variation of APT*/guanidyl* ratio images for 3 representative mice. (B) PET imaging with 18 F-FMISO. ROI quantitative analysis of PET is presented in (C). (D) Ex vivo tumor slice (X20 magnification) stained with pimonidazole and Hoechst. Data were presented by individual values with mean ± SD. Paired t-test (* P = 0.0164) were applied for in vivo quantifications. Red data points on panels (C) correspond to the image shown in (B). Abbreviations: T: Tumor; M: muscle.

FIGURE 1 :

 1 FIGURE 1: z-spectra of (A) chondroitin 4-sulfate and (C) protamine at several concentrations and pH, respectively. The CEST effects were estimated by measuring the AUC from 0.02 to 1.50 ppm for chondroitin 4-sulfate (GAG CEST) and the signal intensity at 1.96 and 3.60 for guanidyl* and APT* CEST, respectively. The relationship between CEST quantification and concentrations or pH are represented on panels (B) and (D), respectively.

FIGURE 2 :

 2 FIGURE 2: In vivo multimodal imaging of GAGs in SRC bearing mice (A) GAG CEST parametric image. To clearly identify the tumor, the high-resolution image was added inside the inset. (C) SPECT-CT imaging with 99m Tc-NTP 15-5. ROI quantitative analysis of GAG CEST and SPECT-CT are presented in (B) and (D), respectively. (E) Ex vivo tumor slice (X20 magnification) stained with both alcian blue and nuclear red. Data were presented by individual values with mean ± SD. Paired t-test and unpaired t-test (**** P < 0.0001) were applied for in vivo and ex vivo quantifications, respectively. Red data points on panels (B), (D) and (F) correspond to the images shown in (A), (C) and (E), respectively. Abbreviations: T: Tumor; M: muscle.

FIGURE 3 :

 3 FIGURE 3: In vivo multimodal imaging of pH acidification (MRI) and hypoxia (PET) in SRC bearing mice. (A) High resolution and relative variation of APT*/guanidyl* ratio images for 3 representative mice. (B) PET imaging with 18 F-FMISO. ROI quantitative analysis of PET is presented in (C). (D) Ex vivo tumor slice (X20 magnification) stained with pimonidazole and Hoechst. Data were presented by individual values with mean ± SD. Paired t-test (* P = 0.0164) were applied for in vivo quantifications. Red data points on panels (C) correspond to the image shown in (B). Abbreviations: T: Tumor; M: muscle.

ACKNOWLEDGEMENTS The authors thank Christelle Damon-Soubeyrand (Anipath facility) for her precious technical help with histological equipment.

SUPPORTING FIGURE AND TABLE CAPTIONS Supporting Table

 S1: Overview of the experimental design and analysis by in vivo modality. Supporting


Rutvik Chauhan
email: rchauha1@ualberta.ca

Utkarsh Pandey
email: upandey@ualberta.ca

Real-Time Cow Counting From Video or Image Stack captured from a Drone

Keywords:

With the increase in amount of cows in large farm, the demand increases to monitor cows as well as the difficulty to hire a labor to monitor the cows. Due to recent advancements in technology, remote monitoring system can be more reliable using some tags or using computer vision system which can yield more accurate and valuable information about an animal. Also the information about it's behaviour and surrounding environment can be obtained. Using which we can maximize production.

I. INTRODUCTION

For large amount of cows and in a large area, counting cows can be tedious task to do for a human.Instead automatic monitoring system can be used for counting cows from video or stack of images. Video or stack of images can be gathered from a drone and we need to detect each cow, color each detected uniquely identified cow and evaluate the performance between video and stack of images.

II. RELATED WORK

A. Automatic Cow Counting

In [Sha+20], authors used Convolutional Neural Network(CNN) to detect and count cattle from Unmanned Aerial Vehicle(UAV) imagery. The algorithm proposed by author takes the following steps: 1) Detect cattle in each image. 2) Reconstruct the 3D surface of the pasture by Structure from Motion(SfM) from the same set of images. With the candidate bounding boxes, the 3D surface, and the relative position of the cameras.3) Merge the per frame detection results guided by the 3D surface. Through this merging over time, the double detection of single cows are eliminated and the correctly counted number of cows is obtained.In [Xu+20], authors used maskrcnn to detect and classify cattle and sheep and to count the total numbers from aerial images taken from quadcopter. Object Detection: In [BWL20], authors achieved 43.5 percent AP (65.7 percent AP50) for the MS COCO dataset at a realtime speed of around 65 FPS on Tesla V100. Instance Segmentation: In [He+17], authors proposed MaskRCNN method for object instance segmentation. For instance segmentation [Bol+19a] and [Bol+19b] achieved realtime performance with good accuracy. In [Bol+19a], authors presented a simple, fullyconvolutional model for realtime instance segmentation that achieves 29.8 mAP on MSCOCO at 33.5 fps evaluated on a single Titan Xp.

1) Implemented algorithms from existing work: For automatic monitoring system, cow detection and numbering can be implemented using computer vision or deep learning methods. As seen in literature, traditional computer vision approaches yield less accuracy. To get the state-of-the-art performance, deep learning based methods can be used. For object detection and instance segmentation, there are many state-ofthe-art models and architectures available.The following was a part of the analysis done by our team. a) Use moving labels/Tags to number the moving cows in a segment of the video (bounding box or segmented cow).b) Segment the cows when they are packed together.c) Label cows entering the view.d) Ensure the label is not reallocated(duplicate) for the cow which re-enters the scene.e) Store unique features and neighbourhood information using a complex data structure to connect two scenes where camera viewpoint changes. The proposed solution can be used in other domains/applications for example-unique vehicle identification, cargo tracking on the docks, and so on. There are certain points that can be considered as challenges involved in this project such as -a) Both the cows and camera(drone) are moving.b) Segment the cows when they are too close to each other.c) Resolution of the camera fit on the drone is not able to display the tag numbers of the cow's ears.The expected deliverable is feasible if the videos used in the experiments are not overly challenging.Two major milestones that can be considered here would be 1) Counting with cows entering and leaving the view, but without re-entering.

2) Take a short video clip with cow(s) re-appearing in view and introduce additional parameters or data structures to avoid duplicate counting.

B. Review of Other published papers 1) Gradient Vector Flow based Active Shape Model for

Lung Field Segmentation in Chest Radiographs: [START_REF] Xu | Gradient vector flow based active shape model for lung field segmentation in chest radiographs[END_REF]Accurate lung field segmentation is crucial to computer-aided diagnosis (CAD) of lung diseases such as lung cancer and tuberculosis Interestingly to point out, the proposed solution shows a GVF-ASM method with exponential points evolution for lung field segmentation. The experimental results demonstrated that the proposed method improves the robustness and accuracy of the segmentation.

2) Pose Recognition using the Radon Transform: [START_REF] Singh | Pose recognition using the radon transform[END_REF]Human pose recognition is an active topic of vision research that has applications in diverse fields such as collaborative virtual environments and robot tele-operation. The proposed paper talks about a novel method for the recognition of human pose using the Radon transform. A binary skeleton representation of the human subject is computed and information concerning the pose is extracted from the parametric Radon transform. The Radon transform generates maxima corresponding to specific orientations of the skeletal representation. A spatial maxima mapping technique is developed to recognize pose from the Radon transform maxima. This technique has the potential to provide information about the exact orientation of pose segments. Experiments with real image data highlight the advantages of this approach.

In this paper, an algorithm for the recognition of human poses and gestures using the Radon transform is proposed. While there are other template-based approaches in contemporary literature that are being used for pose recognition, these approaches are computationally more expensive and also require normalization of the images. The proposed approach on the other hand does not require any normalization and also guarantees a higher resolution of recognition for arm and leg poses. The promising recognition rates achieved with the parameterized Radon transform emphasize the feasibility of the proposed method. In the future we plan to use the orientation information derived from the Radon transform space to reconstruct motion for virtual models.

3) Omni-directional sensors for pipe inspection: [START_REF] Basu | Omni-directional sensors for pipe inspection[END_REF]Omnidirectional sensors are useful in obtaining a 360" field of view with a single lens camera. At present, for inspecting the interior of pipes (used in industrial processes) fish-eye type lenses are being used. However, fish-eye lenses provide more detail on the empty center part of the pipe and less detail on the surface of the pipe near the camera. This problem can be resolved by using an omni-directional camera, which projects a cylindrical strip of the interior surface of a pipe to a single CCD device. A description of the hardware developed and experimental results are presented.

The use of a conical mirror presents several unusual problems, each of which must be addressed if image quality is to remain high.In theory, the non-planar mirror distortion could be corrected through de-convolution postprocessing. In practice, this approach is problematic; the process is very computationally intensive -especially since the deconvolution basis function is not constant, but is itself a function of the position within the image. This is due to the fact that the radius of curvature changes with distance to the conical apex.

There are several approaches to deal with the low sampling frequencies found at the centre of the CCD : 0 By introducing a curve to the radial profile of the conical mirror, it is possible to obtain complete control over the effective spacial acuity at any given elevation. Factoring in the non-planar distortion, it is then straightforward to control one source of acuity failure with respect to the other,yielding a uniform image quality across all elevations.e The centre of the cone can be truncated, and conventional wide-angled optics installed within the cone, along its axis (Figure 11). This arrangement can usefully employ the otherwise wasted CCD area by providing a forward view to complement the scope of the reflective cone. An almost complete 4.rr steradians field of view is possible Colour information can often be represented at spatial frequencies rather lower than those of luminance information (eg. broadcast video standards).Another potential use tion of the cone would be t formation from the inside of the pipeline, using 3 coloured bands applied to the cone. Since the camera will be propelled through the pipe, a fixed point on the surface of the peach distance from the centr is passed by the probe. By monitoring the differential intensities of the light arriving on the (monochrome) CCD as it sweeps through red, green, and blue regions of the cone, postprocessing could reconstruct a full colour representation of the imaged surface. This technique may well prove particularly important, as a feature common to all very wide angle optical systems is that the acuity is very often limited by the CCD devices. Extracting colour from a monochrome device would allow a much higher device resolution.

4) Eye Tracking and Animation for MPEG-4 Coding: [START_REF] Bernogger | Eye tracking and animation for mpeg-4 coding[END_REF]Accurate localization and tracking of facial features are crucial for developing high quality model-based coding (MPEG-4) systems. For teleconferencing applications at very low bit rates, it is necessary to track eye and lip movements accurately over time. These movements can be coded and transmitted to a remote site, where animation techniques can be used to synthesize facial movements on a model of a face. In this paper we describe simple heuristics which are effective in improving the results of well-known facial feature detection and tracking algorithms. Animation models are also presented, along with experimental results to demonstrate the system being developed. the focus is on the discussion only on the detection, tracking and modeling of eye movements 5) Stereo Matching Using Random Walks: [START_REF] Shen | Stereo matching using random walks[END_REF]This paper presents a novel two-phase stereo matching algorithm using the random walks framework. At first, a set of reliable matching pixels is extracted with prior matrices defined on the penalties of different disparity configurations and Laplacian matrices defined on the neighbourhood information of pixels. Following this, using the reliable set as seeds, the disparities of unreliable regions are determined by solving a Dirichlet problem. The variance of illumination across different images is taken into account when building the prior matrices and the Laplacian matrices, which improves the accuracy of the resulting disparity maps. Even though random walks have been used in other applications, our work is the first application of random walks in stereo matching. The proposed algorithm demonstrates good performance using the Middlebury stereo datasets.

One crucial and traditional task in stereo vision is stereo matching, the goal of which is to determine the disparities of corresponding pixels in a pair of stereo images.A recent application of random walks (RW) in multilabel image seg-mentation shows great potential for its application in stereo matching.The major advantage of random walks is that an exact and unique minimum solution of an energy function of the above form can be produced, while other approaches like GC can only produce an approximation. Therefore, it is very likely that RW can achieve better performance than GC and other optimization frameworks in stereo matching. Hence, we develop a new stereo matching algorithm using random walks. Our contribution lies in that our work is the first application of random walks in the area of stereo matching. Two major phases are considered: first, a set of reliable matching pixels is computed using RWwith prior models (Section 4); second, with the reliable set serving as seeds, the disparities of unreliable pixels are determined using the original RW [START_REF] Bernogger | Eye tracking and animation for mpeg-4 coding[END_REF] (Section 5). As demonstrated in Section 6, our algorithm produces more accurate disparity maps than many of GC-based and DP based methods, and some of BPbased methods. In the future, there is a plan to incorporate segmentbased methods to label a more reliable set of initial matching pixels, which will be used to initialize the random walks optimization procedure. This combination, together with GPU implementation, will achieve a much more accurate and faster disparity estimation.

6) Variable-resolution character thinning: [START_REF] Li | Variable-resolution character thinning[END_REF]Character thinning is often used as a prepossessing step for character recognition. The input to a thinning algorithm is a binary image of a character. The pixels with value 1 form the character (object) and the pixels with value 0 form the background. The strokes of the input character are several pixels thick. The objective of thinning is to generate the skeleton of the character in order to achieve information reduction and extraction for further recognition.

The algorithm is parallel in nature and some computation techniques are reported.The result of the proposed method show some significant improvements on several characters in the experiments.More experiments are being conducted to improve the behavior of thinning algorithm on different corners of the character.

7) Automatic Segmentation of Spinal Cord MRI Using Symmetric Boundary Tracing: [START_REF] Mukherjee | Automatic segmentation of spinal cord mri using symmetric boundary tracing[END_REF]An adaptive active contour tracing algorithm for extraction of spinal cord from MRI that is fully automatic is developed, unlike existing approaches that need manually chosen seeds. One can accurately extract the target spinal cord and construct the volume of interest to provide visual guidance for strategic rehabilitation surgery planning.

An image of a typical 2-D spinal cord slice is shown in Fig. 1(a). The contrast of the pixels representing the spinal cord in a 2-D slice is distinctly different with respect to the pixel values of the vertebra bone and muscles seen in the image. The segmentation result of the spinal cord is shown in Fig. 1(b). Given that the spinal cord is identified, a technique for the image unskewing process, which is a precursor to the segmentation of other target regions is presented.

The two major proposals of this paper are the symmetry line estimation followed by the active tracing approach. The 2-D image slices of spinal cord MRI was acquired with a 2-D spoiled gradient echo sequence operating in multi-slice mode.The proposed paper talks about an automatic spinal cord image segmentation approach in order to assist rehabilitation surgery planning process.Differing from other semiautomatic techniques that extract only the spinal cord, our approach segments the neighboring regions of interest providing better visual guidance for ISMS implant. The methodology introduces a novel application of active tracing of segment boundary,the evolution of which is implemented on a unique contour energy minimization surface.

8) Interactive Multimedia for Adaptive Online Education †: [START_REF] Cheng | Interactive multimedia for adaptive online education[END_REF]Interactive multimedia content has the capability to improve learning performance by enhancing user satisfaction and engagement. Multimedia content also provides better concept representation, which is not possible in conventional multiplechoice and fill-in-the-blank formats.This article, presents a broader view of multimedia education especially for the years to come. The vision is to provide publicly accessible education anywhere, at anytime and to anyone. We propose an innovative CROME (Computer Reinforced Online Multimedia Education) framework integrating the main components of education including learning, teaching and testing, as well as adaptive testing and student modeling.

The unique contributions of the system are: Automatic difficulty level estimation for selected subjects, compared to estimates based on user group calibration ; Adaptive testing using innovative item formats versus using traditional multiple choice items (Moodle's multiple choice, GMAT). Computer-assisted automatic question item authoring, rather than manually creating different questions; Custom-designed modules for tracking precise concepts that are lacking in recommendation systems; and, Ability for testing beyond only subject knowledge, unlike other e-learning systems.

The design of CROME aims to achieve portability, reusability, scalability and interoperability:1) Portability -The implementation is based on Java which is platform independent, including J2ME on mobile devices. 2) Reusability -An object-oriented design makes individual components reusable. 3) Interoperability -An authoring tool is an integral part of the CROME system, sharing the item type design, as well as media and item database. 4)Scalability -New item type plug-ins can be added without the need to modify the basic framework or authoring module. 9) Variable Resolution Teleconferencing: [START_REF] Basu | Variable resolution teleconferencing[END_REF]Images can contain a large amount of information, which in turns increase the size of the image. To make teleconferencing efficient over bandwidth, some kind of compression technique needs to be implemented. There are mainly 2 types of compression techniques-lossy and lossless. Studies have shown that humans tend to have more focus on the center of the image. Authors have proposed a compression method based on these studies in which the image has higher resolution in the center of the image and lower resolution in the periphery of the image. Authors proposed different variable resolution models. First one was a basic variable resolution model which has 2 parameters-the expected savings (compression) and alpha (which controls the distortion at the edges of the image with respect to the fovea). Second model was Extended model with movable fovea, in which multiple scaling factors are used. Third model was for multiple foveas where two or more regions are displayed with higher resolution than the remainder of the image. Authors listed 3 measures which are important in determining the importance of a compression method: the compression ratio, compression time, resulting image quality. When global image quality is considered, the optimal alpha value differs according to the compression ratio used. On a SUN SpaRC Station SLC, time measured on the CPU for compression using the proposed method was in the range 0.05 to 0.15 seconds. In conclusion, a videoconferencing system is a primary application for virtual resolution as it requires fast compression of images, image quality is not a high priority, typical talking head scene provides for an ideal fovea location. Time of execution of the proposed algorithm made it ideal for the teleconferencing market.

10) A Framework for Adaptive Training Games in Virtual Reality Rehabilitation Environments: [START_REF] Rossol | A framework for adaptive training and games in virtual reality rehabilitation environments[END_REF]For the conventional rehabilitation technique and equipment available had very limited time per patient for training. Studies showed that Virtual Reality games engaged patients which leads to longer training time overall. Another limitation is the cost of the electric power wheelchair is high and it was also not flexible in terms of transportation. Specialists available for this type of training were also very limited. Authors proposed a system which had unique features. The system was designed to be low-overhead, portable and focused on indoor training environments. System provides a framework which allows clinicians to design, build and customize interactive indoor rehabilitation training environments which act as a realistic environment. Another challenge is that a simple virtual re-ality system did not provide any change over time as the patient's abilities changed. Authors proposed a novel flexible, adaptive framework based on Bayesian Network which allows clinicians to measure performance of the patients and change the difficulty overtime. The system automatically assesses a complex range of patient skills. Evaluation of the system was done with 8 people aged between 22 to 28 year. They are divided in 2 groups: experimental and control. Experiment group has access to a proposed system which enables people to complete challenges in an average time of 81.5 seconds. The control group's time to complete the challenges were around 104.5 seconds. Rehabilitation specialists and clinicians provided positive feedback for the proposed system.

11) Panoramic Video with Predictive Windows for Telepresence Applications: [START_REF] Baldwin | Panoramic video with predictive windows for telepresence applications[END_REF]Ability to perform tasks in a remote environment is becoming more widely desired in robotics related applications. Telepresence systems provide an immersive impression of the remote site environment to human operators. A typical telepresence system includes a human operator with a control interface, a remote robotic system and a means of communicating between the two systems. Bandwidth for the local and remote systems needs to be sufficient to transmit the sensory and control data. In a limited bandwidth environment, it is very important to decide which fragment of a frame is to be transmitted. Authors proposed using a predictive Kalman filter to model mouse motion in controlling a predictive window. In this paper, author proposed applying the same predictive technique to a panoramic imaging system and consider the problem of parameter identification in the prediction process. Authors also discussed using a Kalman filter to predict viewing direction when displaying panoramic images in a telepresence system. Mouse was used as an input device using which the viewing window around in a panoramic video moved. Operator only saw a fragment of a panoramic image that is contained within this viewing window. Authors' model assumes that the mouse can be modeled as a point mass under the influence of a constant external force and subject to fractional resistance. The panoramic video system using the proposed method, authors used a camera which had been fitted with a mirror to provide panoramic video. The 360 degree panoramic video allows an immersive feel. The prediction method determines where the mouse is moving so that system can prepare for the operator's viewing habits to reduce the apparent response delay. Prediction model generally produced a smaller mean distance error than no prediction and the new error modeling improved still further. The research presented used a low resolution imaging system, so overall performance can be increased using higher resolution imaging system.

12) Videoconferencing using Spatially Varying Sensing with Multiple and Moving Foveae: [START_REF] Basu | Videoconferencing using spatially varying sensing with multiple and moving foveae[END_REF]In this paper, a new method for videoconferencing for spatially varying sensing is introduced. Authors proposed a variable resolution system for the compression of the video to transmit it over low bandwidth system. The basic variable resolution model has two parameters-compression and alpha. Basic variable resolution model is extended to use multiple scaling factors to deal with non-rectangular compressed images. Advantage of this method is that the tables need not be recomputed each time the fovea changes the location. In some circumstances there could be more than one area of interest to the observer, which is multiple foveae. There are two distinct approaches for this-cooperative foveae and competitive foveae. In cooperative foveae, it calculates the location of a point in the transformed image with respect to each fovea separately. In competitive foveae, all foveae compete to calculate the position of a point in the transformed image. The fovea which is closest to point in the original image will determines transformed position. Authors also included a videophone prototype using the proposed method which has the interface as shown below in the figure . Local region growing algorithm is used to determine local area of features. To detect nostril shape, a geometric template is applied on the nostril region, which is a twisted pair curve with a leaflike shape. After detecting all the feature regions and estimating shape on various organs, a 3D wireframe model can be matched onto the individual face to track the motion of facial expression. Experimental results are shown in the figure below. Initial results show that this approach is feasible in practical applications.

14) Integrating active face tracking with model based coding: [START_REF] Yin | Integrating active face tracking with model based coding[END_REF]In real situations, detection and tracking of the active talking face is a fundamental step. To compress face-to-face video communication, segmenting and tracking a talking face from a background is a prerequisite. In a movable background, it is difficult to segment the background. In this paper, authors presented a system to track talking faces with an active camera. Proposed system can implement the face detection, tracking, adaptation and animation automatically. To recover the speaker's silhouette it is necessary to extract it from a number of successive frame differences. To detect eyes and mouth, authors used a deformable template matching. Based on position of the eyes and mouth, position of the head is detected and their shapes can determine the facial expressions. In conclusion, authors proposed a system to track a face with an active camera for an arbitrary background.

15) Modeling Fish-Eye Lenses: [START_REF] Shao | Cattle detection and counting in uav images based on convolutional neural networks[END_REF]We as a human tends to have a variable resolution in our visual system. Foveal image has higher resolution, whereas peripheral information has lower resolution. Existing variable-resolution transforms are very expensive to compute and need special sensors to replicate variable resolution. Authors proposed a Fish Eye Transform which is based on a simplification of the complex logarithmic mapping. Disadvantage of this is that it produces strong anisotropic distortions in peripheral regions. Authors also discussed polynomial fish eye transform to eliminate this problem. Authors also proposed fish eye lenses, using which the objective became to find a function that represents the average distortion calculated. In experiments, the polynomial model appeared to have a better performance in compensating the distortions.

Fig. 1 .Fig. 2 .

 12 Fig. 1. Comparison between yolact, yolo, tensorflow object detection api, amazon rekognition

Fig. 3 .

 3 Fig. 3.

Fig. 4 .

 4 Fig. 4. Videophone prototype

Fig. 5 .

 5 Fig. 5.