P Carminati

T Buffeteau

N Daugey

G Chollon

F Rebillat

S Jacques

Low Pressure Chemical Vapour Deposition of BN: relationship between gas phase chemistry and coating microstructure

Keywords: Boron nitride, Boron trichloride, Aminodichloroborane, Dichloroborane, Effective precursor, Crystallization degree, Structural homogeneity, Fourier-transform Infrared spectroscopy

The structural and morphological characteristics of flat BN coatings processed by chemical vapour deposition, using BCl3-NH3-H2 gas mixtures at low pressure (P < 1 kPa), have been investigated as a function of the deposition temperature (ranging from 900 °C to 1400 °C) and the total gas flow rate. The resulting BN coatings are mainly turbostratic but with heterogeneous microstructures, i.e. mixtures of poorly and highly organized domains. The structural homogeneity and the degree of crystallization depend notably on the nature of the dilution gas (either H2 or Ar) and the depletion of gas species. The decrease of the apparent activation energy from 80 kJ.mol -1 below 1200 °C to 40 kJ.mol -1 above 1200 °C reflects a change in the deposition regime. Ex situ Fourier transform infrared analysis of the residual gas mixture allowed intermediate species leading to poorly or highly organized BN to be tracked and then connected with the main reaction paths leading to the different BN coatings.

Introduction

Because of its attractive properties, hexagonal BN is a useful material for a wide range of applications [START_REF] Eichler | Boron nitride (BN) and BN composites for high-temperature applications[END_REF]. Being isoelectronic with carbon and having a similar structure while exhibiting a better oxidation resistance, BN is considered for improving the performance of carbon/carbon composites [START_REF] Cofer | Economy, Oxydation and hydrolitic stability of boron nitride. A new approach to improving the oxidation resistance of carbonaceous structures[END_REF] [3]. Boron nitride is also a promising alternative to pyrocarbon as an interphase in ceramic matrix composites (CMCs) aimed at the next generation of aircraft engines. Indeed, the use of BN interphase could improve the mechanical properties and lifetime of SiC-based CMCs under oxidative environment at high temperature [START_REF] Evans | The Structural Performance of Ceramic Matrix Composites[END_REF] [START_REF] Naslain | The design of the fibre-matrix interfacial zone in ceramic matrix composites[END_REF] [6] [START_REF] Morscher | Effect of a boron nitride interphase that debonds between the interphase and the matrix in SiC/SiC composites[END_REF]. The method and the parameters used to process BN are key points affecting the degree of crystallization and therefore the properties of the resulting material [START_REF] Cofer | Economy, Oxydation and hydrolitic stability of boron nitride. A new approach to improving the oxidation resistance of carbonaceous structures[END_REF]. When the as prepared BN is poorly organized, an additional heat treatment is sometimes needed to achieve better performance [START_REF] Udayakumar | Effect of intermediate heat treatment on mechanical properties of SiCf/SiC composites with BN interphase prepared by ICVI[END_REF] [START_REF] Sun | Controllable coating of boron nitride on ceramic fibers by CVD at low temperature[END_REF].

The main way to produce a BN interphase coating of uniform thickness around ceramic fibres is chemical vapour deposition (CVD) or alternatively chemical vapour infiltration, in case of a porous fibrous substrate as in composites. Different gas mixtures have been employed to deposit BN by CVD such as BF3-NH3 [START_REF] Prouhet | An experimental kinetic study of boron nitride CVD from BF3-NH3-Ar mixtures[END_REF] [START_REF] Rebillat | Highly ordered pyrolytic BN obtained by LPCVD[END_REF] [START_REF] Jacques | Multilayered BN Coatings Processed by a Continuous LPCVD Treatment onto Hi-Nicalon Fibers[END_REF], borazine-based or borane-based precursors [START_REF] Sun | Controllable coating of boron nitride on ceramic fibers by CVD at low temperature[END_REF] [13] [START_REF] Stolle | Deposition of Boron Nitride Films from BB'B"-Trichloroborazine[END_REF] [START_REF] Jacques | BN Interphase Processed by LP-CVD from Tris(Dimethylamino)Borane and Characterized using SiC/SiC Minicomposites[END_REF] [16] [START_REF] Wu | Deposition of BN interphase coatings from Btrichloroborazine and its effects on the mechanical properties of SiC/SiC composites[END_REF] and BCl3-NH3 [START_REF] Pavlovic | Chemical vapor deposition of boron nitride using premixed borontrichloride and ammonia[END_REF] [19] [START_REF] Matsuda | Density and deposition rate of chemical-vapour-deposited boron nitride[END_REF] [START_REF] Cholet | Chemical Vapor Infiltration of Boron Nitride Interphase in Ceramic Fiber Preforms: Discussion of Some Aspects of the Fundamentals of the Isothermal Chemical Vapor Infiltration Process[END_REF]. Generally, BN coatings can be well organized when the deposition temperature exceeds 1000 °C. When using the first system, however, the main gaseous reaction product, HF, causes serious damages to the SiC fibres during BN deposition. Borazine/borane-based precursors are not corrosive and do not cause any substrate damage, but these species are expensive and sensitive to moisture. The use of BCl3 as the initial boron source leads to HCl as a gaseous by-product, which is less aggressive than HF towards SiC-based substrates. For these reasons, BCl3-NH3 has been widely used for more than twenty years for the CVD of BN. The gas-phase reactions occurring from this system are complex. Thermodynamic calculations and plug-flow predictions have shown that BCl3 and NH3 can react from 500 °C to form intermediate species containing boron and nitrogen, some of which being possible effective precursors of BN [START_REF] Hannache | Boron nitride chemical vapour infiltration of fibrous materials from BCl3-NH3-H2 or BF3-NH3 mixtures: A thermodynamic and experimental approach[END_REF] [START_REF] Allendorf | A Model of the Gas-Phase Chemistry of Boron Nitride CVD from BCl3 and NH3, in Covalent Ceramics III-Science and Technology of Non-Oxides[END_REF]. Intermediate gas species could be detected at the outlet of a CVD reactor using the technique of modulated molecular-beam mass spectrometry [START_REF] Mcdaniel | Flow-Tube Investigation of the High-Temperature Reaction between BCl3 and NH3[END_REF]. Their concentrations were correlated with changes in the deposition rate and the nature of homogenous and heterogeneous reactions that are responsible for the BN growth

The aim of the present study is to establish the relationship between the nature of the different intermediate gas species involved in the low pressure CVD (LPCVD) of BN from BCl3-NH3 gas mixtures and the type of regime controlling the growth and the coating microstructures. Fouriertransform infrared (FTIR) spectroscopy has been successfully used in previous CVD studies with other chemical systems [25] [26] [27]. This technique has been used here to detect, identify and follow the concentration of the species present in the gas phase at the reactor outlet. The growth rates have been measured and the local chemical environment and crystalline structures of the BN coatings have been characterized. By studying the influence of the temperature, the nature of the carrier gas and the gas flow rate, this work aims at a better understanding of the reaction mechanism involved in the growth of BN.

Experimental

Deposition

The apparatus used to deposit the BN coatings was a LPCVD hot-wall tubular reactor (Fig. 1). This reactor was a 110 cm long graphite tube having a central portion heated by an induction coil. BCl3 (purity 99.99%) and NH3 (purity 99.99%) gases were used as BN precursors and H2 (purity 99.99%) or Ar (purity 99.99%) for dilution. The total pressure P (in the reactor) was set below 1 kPa, the gas phase composition ratio α = PNH 3 /PBCl 3 above 1, and the dilution ratio, β = Pdiluent gas / (PBCl 3 + PNH 3 ) at 10. The total gas flow rate Qtot and the deposition temperature T were varied whereas other parameters were kept constant. Since BCl3 readily reacts with NH3 at room temperature to form a white powder of Cl3BNH3, these gases were introduced separately into the CVD reactor. BN coatings were deposited on the rough side of 5 mm x 5 mm silicon wafers to promote a better coating adhesion. All the deposited coatings are thicker than 1 µm.

Coating characterization

Coating thicknesses were measured from fractured surfaces by Scanning Electron Microscopy (SEM, QUANTA 400 FEG). The average growth rates were obtained at the end of the experiment from the deposition durations. The outer surface morphology of as processed coatings was also observed by SEM.

The coating microstructure was characterized through Transmission Electron Microscopy (TEM) (Philips CM30ST) and X-Ray Diffraction (XRD) (θ/θ diffractometer Brucker D8 Advance λCuKα1 = 0.15419 nm). TEM images were obtained using the dark field or high resolution mode. XRD patterns were acquired on a 2θ range of 20-30°, in order to focus analysis on the peak related to the diffraction from adjacent basal planes of sp 2 -hybridized BN (sp 2 -BN) corresponding either to (002) for hexagonal BN (2θ = 26,765°, JCPDS n° 00-034-0421) or to (003) for rhombohedral BN [START_REF] Chubarov | Review Article: Challenge in determining the crystal structure of epitaxial 0001 oriented sp 2 -BN films[END_REF]. The degree of crystallization of the coatings was estimated from Lc (coherence length) and d (interreticular distance between the sp 2 -BN basal planes). Lc was calculated from the Scherrer equation: Lc = kλ / Γcos(θ), where the constant k was taken equal to 0.9, Γ is the full width at half maximum of the XRD peak, λ is the wavelength of CuKα1 line and θ is the diffraction angle. d was deduced from Bragg's law: 2d sin(θ) = nλ, where n is the diffraction order taken equal to 1.

The XRD peaks of BN coatings are often asymmetric (Fig. 2). This asymmetry was attributed to the coexistence of poorly and highly organized domains in the coatings. This results in a larger half width at half maximum for 2θ < 2θImax (left red segment in Fig. 2) than the half width at half maximum for 2θ > 2θImax (right blue segment in Fig. 2). In order to quantify this asymmetry, a factor (η) was defined as the half width at half maximum for 2θ > 2θImax divided by the half width at half maximum for 2θ < 2θImax. When the peak is symmetric, η is 1.

Finally, X-Ray Photoelectron Spectrometry (XPS) measurements have been carried out in order to control the purity of coatings and identify the chemical environments of boron atoms (ThermoFisher Scientific spectrometer, Al source 1486.6 eV). The B1s XPS spectra were fitted using Avantage Software TM .

Gas phase characterization

The reactor outlet was connected to a FTIR spectrometer (Thermoscientific IS50) (Fig. 1). The cooled down gas mixture, evacuated from the reactor outlet, passed through a 60 cm long analysis column. The IR beam was directed towards the entrance window (ZnSe) with a mirror. The incident parallel beam passed axially through the gas column at room temperature, integrating the transmission signal (all the precursors and gas products are thermally stable). The output IR beam was focused by mirrors on an HgCdTe MCT-A detector cooled by liquid nitrogen. The detectors and the whole IR beam path were purged with a nitrogen flow to prevent H2O and CO2 absorption.

FTIR spectra were collected from 650 to 4000 cm -1 . A background spectrum was collected just before sample analysis by replacing the reactive gas mixture with pure H2 or Ar. It is well known that the concentration of a given species depends linearly on the total area of a characteristic absorption peak (Beer Lambert law).

Theoretical calculations of IR spectra

The geometry optimizations, vibrational frequencies and absorption intensities were calculated with Gaussian 09 program [START_REF] Frisch | Gaussian 09[END_REF] on the Gaudi cluster of the "Pôle Modélisation" computer centre of the Institute of Molecular Sciences (University of Bordeaux). The calculation of the optimized geometries of Cl3BNH3, Cl2BNH2, BCl(NH2)2, B(NH2)3 and Cl-B=N-H [START_REF] Allendorf | A Model of the Gas-Phase Chemistry of Boron Nitride CVD from BCl3 and NH3, in Covalent Ceramics III-Science and Technology of Non-Oxides[END_REF] was performed at the density functional theory level using the B3LYP functional [START_REF] Lee | Development of the Colle-Salvetti correlation-energy formula into a functional of the electron density[END_REF] [31] and cc-pVTZ basis set. The vibrational frequencies and IR intensities were calculated at the same level of theory. To obtain a detailed assignment of each compound, the potential energy distribution (PED) for each mode has been determined with the VEDA 4 software [START_REF] Jamroz | Vibrational Energy Distribution Analysis VEDA[END_REF].

Results

Coating analysis

4.1.1. Growth rate from BCl3-NH3-H2 gas mixtures At 1200 °C and for Qtot < 300 sccm, the growth rate increases with the total flow rate (Tab. 1), indicating a mass transport limited regime. In contrast for Qtot > 300 sccm, the coating growth rate becomes independent of the gas flow rate, in agreement with a surface reaction-limited regime.

For Qtot = 360 sccm, the growth rate increases with the temperature in the range of 900-1400 °C (Tab. 1). Two slopes are visible on the Arrhenius plot shown in Fig. 3, with a transition occurring at about 1200 °C. This feature can be attributed to a change in the global deposition mechanism.

The first domain below 1200 °C should correspond to a reaction-limited regime, with an apparent activation energy Ea equal to 80 kJ.mol -1 . As a comparison, Cheng et al. [START_REF] Cheng | BN coatings prepared by low pressure chemical vapor deposition using boron trichloride-ammonia-hydrogen-argon mixture gases[END_REF] found a value of 125 kJ.mol -1 in the range of 650-1000 °C, whereas Ye et al. [START_REF] Ye | Investigation of boron nitride prepared by Low Pressure Chemical Vapor Deposition at 650~1200 °C[END_REF] obtained 113 kJ.mol -1 in the range of 650-800 °C using the same gas system (BCl3-NH3-H2). The lower apparent activation energy may arise from the different deposition parameters used here, such as the pressure and dilution ratio. Indeed, the pressure chosen in the present work was lower than the pressure of 1 kPa used by Cheng et al. and β was five times higher. In the study of Ye et al. the pressure was lower than 1 kPa but the dilution ratio was not given, making the comparison difficult. Given that these parameters can have a significant effect on CVD kinetics, such differences could account for the discrepancies in Ea values.

The decrease of Ea to 40 kJ.mol -1 observed above 1200 °C should correspond to a mass transport-limited regime, at least in part, because the effect of temperature on the growth rate becomes less important. The influence of the total gas flow rate at 1200 °C evidences that this temperature corresponds to a transition between both regimes. The activation energy of 11 kJ.mol -1 measured by Ye et al. [START_REF] Ye | Investigation of boron nitride prepared by Low Pressure Chemical Vapor Deposition at 650~1200 °C[END_REF] in the range of 800-1000 °C was attributed to a mass transport limited regime. These authors also reported that the growth rate decreases because of gas phase nucleation occurring above 1000 °C. In the present work, the decrease of Ea is obtained only in the range of 1200-1400 °C. This suggests that the possible gas phase nucleation and the resulting precursor depletion are expected to occur at much higher temperature than for the study of Ye et al.

Surface morphology of the coatings from BCl3-NH3-H2 gas mixtures

With Qtot = 360 sccm, the surface roughness of the coatings increases for deposition temperatures above 1200 °C (Fig. 4). This change in surface morphology is in line with the change in deposition regime identified above. At 900 °C, white nodules appear on the coating surface in the SEM images after a 24-h exposure to ambient air. The poor chemical stability of BN films deposited from BCl3 and NH3 at low temperature in the presence of moisture has been reported by several authors [35] [36]. The hydrolysis of BN by moisture leads to the formation of ammonium borate hydrate crystals whose appearance corresponds to the particles observed here. This instability may originate from unreacted BN gaseous precursors (NH3 and BCl3) that are trapped within the coating and react with H2O. For deposition temperatures above 900 °C, these nodules are no more detected indicating a better coating stability. 4.1.3. Chemical and crystal structure of the coatings from BCl3-NH3-H2 gas mixtures At a deposition temperature of 1200 °C, the degree of crystallization and η both decrease as the total gas flow rate increases (Fig. 5.a) (Tab. 1). Keeping in mind that when the η ratio is well below 1 the asymmetry of the BN XRD peak is high, these results show not only that the coating exhibits a poor structural homogeneity, but that it becomes even worse as the gas residence time is decreased.

With Qtot = 360 sccm, the degree of crystallization increases with the deposition temperature (Fig. 5.b). At high temperature (T > 1200 °C), the coatings exhibit an interreticular distance d as low as 0.336 (± 0.001) nm and a coherence length Lc as high as 12.0 (± 0.1) nm. These values approximate d = 0.334 (± 0.001) nm and Lc = 11.8 (± 0.1) nm, obtained from a commercial boron nitride supplied by Advanced Ceramics, also processed by CVD from BCl3-NH3-H2 gas mixtures but at a temperature of about 2000 °C. Conversely, the structural homogeneity decreases when the deposition temperature increases (Tab. 1). At high temperature, the coatings are clearly made of a mixture of highly and poorly crystallized sp 2 -BN. A similar feature has already been observed by Matsuda et al. [START_REF] Matsuda | Synthesis and structure of chemically vapour-deposited boron nitride[END_REF] and Chubarov et al. [START_REF] Chubarov | Chemical vapour deposition of epitaxial rhombohedral BN thin films on SiC substrates[END_REF]; it was likely enhanced by the use of cold-wall CVD reactors restricting the gas phase maturation and by higher substrate temperatures. Several other authors have also mentioned XRD BN asymmetric peaks in their papers, but this feature is not further discussed [START_REF] Cheng | BN coatings prepared by low pressure chemical vapor deposition using boron trichloride-ammonia-hydrogen-argon mixture gases[END_REF] [START_REF] Gallet | Microstructural and microtextural investigations of boron nitride deposited from BCl3-NH3-H2 gas mixtures[END_REF].

The dark field TEM images reveal only little contrast and show small cones that regenerate all along the growth and do not develop across the entire thickness of the coating deposited at 1200 °C and with Qtot = 360 sccm (Fig. 6.a). The SAD patterns are typical, with their arcs, of a turbostratic material with overall structural anisotropy. HRTEM observations show a mixture of small and large coherent domains into the coating. In the smaller domains the fringes are disordered and poorly developed, while the larger domains contain well-developed parallel fringes corresponding to the basal planes of sp 2 -BN (Fig. 6.b). These HRTEM observations evidence that the structural inhomogeneity occurs on a very local scale.

The average binding energies and proportions of the various B1s components evidenced by XPS, for BN films processed with the same deposition parameters, mainly show the presence of sp 2 B-N bonds for the most part as well as a few B-NO bonds, while the presence of B-C and B-B bonds is respectively hardly and not detected (Tab. 2). Chlorine is never evidenced (< 1%at.). This indicates that nearly pure BN was deposited, even though a slight reaction between the coating surface and moisture has occurred during the air exposure of the samples.

In order to better understand the influence of the precursor gas mixture on the crystal structure of the coatings, an experiment has been carried out by switching the gas entry points in the reactor. NH3 was fed into the reactor with H2 at room temperature, far upstream from the deposition reactor area, whereas BCl3 was injected on its own, closer to the deposition area, at about 700 °C. The coating deposited with switched gas entries exhibits a higher crystallization degree (d = 0.338 (± 0.001) nm and Lc = 8.7 (± 0.1) nm) and a better structural homogeneity (η = 0.6) than the sample obtained in standard configuration (d = 0.339 (± 0.001) nm, Lc = 5.9 (± 0.1) nm and η = 0.5) (Fig. 7). Hence, when H2 is used as the diluent gas, the degree of crystallization and the structural homogeneity of the coatings both vary significantly with the gas entry configuration.

Comparison with deposition from BCl3-NH3-Ar gas mixtures

A coating was deposited using argon as the diluent (or carrier) gas instead of hydrogen, all the other parameters remaining unchanged (α, β, Qtot and T). As shown in Fig. 8, the diffraction peak is a little narrower and more symmetrical. The coating deposited with Ar exhibits a higher degree of crystallization and a better structural homogeneity (d = 0.336 (± 0.001) nm, Lc = 11.5 (± 0.1) nm and η = 0.8) than the specimen deposited with H2. One should note besides that the growth rate is slightly reduced (3.2 (± 0.1) µm/h with Ar instead of 3.5 (±0.1) µm/h with H2). Similar crystallographic parameters are obtained using argon dilution deposition when Qtot is reduced by half. Thus, the total flow rate has no significant effect on the degree of the crystallization and the structural homogeneity of the coatings deposited from BCl3-NH3-Ar gas mixtures.

Gas phase analysis

As the analysis was carried out ex situ at room temperature, the detected molecules are necessarily stable and some of them may result from the recombination of unstable intermediates (e.g. BCl2 and BCl radicals). However, the consumption of BCl3 and NH3, the apparition of new species at the reactor outlet and their possible consumption due to homogeneous or heterogeneous reactions as a function of conditions provide useful information for a better understanding of the CVD process.

From preliminary tests carried out using the BCl3-free system, it has been found that the ammonia proportion detected by FTIR at the reactor outlet decreases with T, it is of 65% after passage through the reactor heated at T = 1200°C with respect to the quantity of introduced NH3. For each temperature studied in this work, the proportion of NH3 at the reactor outlet is the same either with hydrogen or argon dilution. Thus, the kinetic of the thermal decomposition of ammonia can be considered as independent of the nature of these diluent gases.

NH3-free system

To better understand the possible reactions between BCl3 and hydrogen, ex situ FTIR analyses have been first performed with the BCl3-H2 and BCl3-Ar systems.

An experiment has been carried out without ammonia and with a reduced gas flow rate (Qtot = 200 sccm), in order to replicate the reactor inlet conditions encountered upstream from the NH3 injection point (at about 700 °C), when the reactor is run in BN deposition conditions. BHCl2 was previously detected by FTIR by Reinisch et al. in a similar experiment using the BCl3-H2 system at a temperature of 500 °C and a pressure of 1 kPa [START_REF] Reinisch | Experimental and theoretical investigation of BCl3 decomposition in H2[END_REF]. Here, from the same BCl3-H2 gas mixture, BHCl2 is only detected above 650 °C, i.e. only 50 °C below the NH3 injection temperature (Fig. 9.a). However, as shown in Fig. 9.b, HCl bands are visible on the spectrum obtained at a temperature as low as 500 °C, while boron deposition is unlikely to occur below 750 °C [START_REF] Sezgi | BHCl2 Formation during Chemical Vapor Deposition of Boron in a Dual-Impinging Jet Reactor[END_REF]. The only homogeneous reaction that is likely to produce hydrogen chloride is BCl3 (g) + H2 (g)  BHCl2 (g) + HCl (g). Therefore, in the conditions used in this experiment, the BHCl2 formation is expected to start at a temperature as low as 500 °C. Thus, this reaction must be considered for the boron nitride deposition from the full gas system. It should be noted that as expected, HCl is not detected from BCl3-Ar gas mixtures.

Full gas system

With the full gas system, i.e. under the experimental conditions previously used for BN deposition (Qtot = 360 sccm and T = 1200 °C), several new peaks are observed on the FTIR spectrum. In addition to unreacted BCl3, CO2 and HCl are detected as well as an NH4Cl condensate deposited on the cold surfaces at temperatures below 300 °C, including the ZnSe windows of the analysis cell. The presence of CO2 can be explained by the presence of residual air along the IR beam path, despite the nitrogen purge. The calculations of the IR relative intensities and vibrational frequencies of species took from literature [START_REF] Becke | Density-functional thermochemistry. III. The role of exact exchange[END_REF] led to the assignment of aminodichloroborane (Cl2BNH2) (Tab. 3) on the experimental FTIR spectrum (Fig. 10). Cl2BNH2 was already detected by mass spectroscopy by Pavlovic et al. [START_REF] Pavlovic | Chemical vapor deposition of boron nitride using premixed borontrichloride and ammonia[END_REF] and McDaniel and Allendorf [START_REF] Mcdaniel | Flow-Tube Investigation of the High-Temperature Reaction between BCl3 and NH3[END_REF]. An infrared spectrum of Cl2BNH2 in the condensed state produced from the reaction between BCI3 and NH3 was also published by Kwon and McGee [START_REF] Kwon | Aminodichloroborane[END_REF]. The band positions for monomeric aminodichloroborane were then specified by calculation by Reinhardt et al. [START_REF] Reinhardt | Simulation of the Solid State Vibrational Spectra of Aminodichloroborane and Ammonia Boron Trichloride[END_REF] and are in good agreement with ours. It is worth noting, however, that the IR spectrum of this species in the gaseous state was not available in open databases so far. No other species containing boron or nitrogen were detected from the full gas system at the outlet of our reactor. NH3 is obviously depleted by the BN deposition and NH4Cl formation. Whatever the diluent gas (H2 or Ar), similar vibrational modes are observed on the FTIR spectrum. From all the IR features, only one peak ( 1080 cm -1 ) could not be assigned to any known species.

According to the plot shown in Fig. 11.a, the areas of the BCl3 and Cl2BNH2 characteristic peaks decrease as the temperature increases (the reference BCl3 peak area measured at room temperature is 4.12 (± 0.01) a.u.). Meanwhile, no further species is detected, while the growth rate increases as observed previously. Cl2BNH2 can thus be considered either as an intermediate species or as an effective precursor involved in the boron nitride deposition. A change in the slope of the Cl2BNH2 concentration curve is observed at 1200 °C (Fig. 11.a). This feature is related to the change in the deposition regime, as observed previously from the Arrhenius plot. The production and depletion of aminodichloroborane occurring successively as the temperature is raised, seem then to control the overall boron nitride deposition mechanism.

As can be seen in Fig. 11.b, the Cl2BNH2 concentration increases with Qtot and reaches a maximum value for a total flow rate close to 250 sccm. The BCl3 concentration increases together with the Cl2BNH2 concentration up to a total gas flow rate of 250 sccm. It then decreases above 250 sccm, no new species being detected besides. These results are consistent with the change in the BN growth rate. They can be explained by a homogeneous nucleation phenomenon starting at high gas flow rates.

As mentioned earlier, the same IR vibrational modes were detected with both H2 and Ar, indicating that similar species were formed in the reactor with either of the two diluent gases. In contrast, the relative intensities of the Cl2BNH2 and BCl3 characteristic peaks are different. Indeed, as can be noticed in Tab. 4, [BCl3]Ar > [BCl3]H 2, whereas [Cl2BNH2]Ar ≤ [Cl2BNH2]H 2 . Such a difference in the residual concentration of BCl3 is consistent, given that the use of hydrogen instead of argon leads to a higher precursor consumption (through BCl3 reduction) and hence, a higher BN growth rate. The NH3 decomposition rate does not depend on the nature of the diluent gas. In contrast, the higher residual Cl2BNH2 concentration measured when replacing argon by hydrogen, while the deposition kinetics is still rather high, could be due to the existence of another boron bearing species (likely BHCl2) acting as effective precursor of the BN deposit.

Discussion

The results shown in section 4.2 and obtained from FTIR measurements confirm that Cl2BNH2 is key gas-phase precursor to BN as reported in the work of Allendorf et al. [START_REF] Allendorf | A Model of the Gas-Phase Chemistry of Boron Nitride CVD from BCl3 and NH3, in Covalent Ceramics III-Science and Technology of Non-Oxides[END_REF] and later in that of McDaniel and Allendorf [START_REF] Mcdaniel | Flow-Tube Investigation of the High-Temperature Reaction between BCl3 and NH3[END_REF]. As in the latter study, ClBNH was never detected at the outlet of our reactor, although its production from Cl2BNH2 (losing HCl) can be expected at high temperatures in the B-N-Cl-H system [START_REF] Allendorf | Thermochemistry of Molecules in the B-N-Cl-H System: Ab Initio Predictions Using the BAC-MP4 Method[END_REF] or from the BCl3-NH3-H2 system [START_REF] Ren | Thermodynamic study on the chemical vapor deposition of boron nitride from the BCl3-NH3-H2 system[END_REF]. The very short gas resident time in our reactor, due to the very low pressure, does not seem to allow the decomposition of Cl2BNH2 into ClBNH. Therefore, Cl2BNH2 can adsorb on the hot substrate surface and form BN after releasing two HCl molecules in the gas phase. This route seems to be involved in the deposition of boron nitride whatever the nature of the diluent or carrier gas and lead to the simplified reaction path N°1 presented in Fig. 12.a.

Even if not detected from the full original BCl3-NH3-H2 system, BHCl2 is formed from the reaction between BCl3 and H2 upstream from the ammonia inlet (i.e. at temperatures in the range 500-700 °C). BHCl2 is then an additional boron containing species that can react with NH3 (or derived radical species) to form BN. The thermodynamic study conducted by Ren et al. from this system suggests that BHCl2 is a crucial intermediate with, to a lesser extent, BCl, BClNH and BH2Cl [START_REF] Ren | Thermodynamic study on the chemical vapor deposition of boron nitride from the BCl3-NH3-H2 system[END_REF]. The formation of the last three species could not be detected here by FTIR because of their instability or their too low concentrations. However, when the quantity of reagents introduced at the reactor inlet is sufficient, the formation of BHCl2 can lead to the simplified reaction path N°2 presented in Fig. 12.b. BN can then be deposited according to two possible reaction paths from the BCl3-NH3-H2 system, whereas only one route is allowed from the BCl3-NH3-Ar system. In the former case, the addition of path N°2 to N°1 allows a higher growth rate.

The BN obtained using H2 is less organized and homogeneous than the ex-Ar BN. The difference in microstructure can be related to the different highlighted growth mechanisms. When both paths are involved (i.e. with H2 as the diluent gas and high enough total gas flow rates), the resulting coatings are therefore made of a mixture of poorly and highly crystallized boron nitride. With a total gas flow rate that is 4 times smaller than that used in standard conditions, the crystallization degree and the structural homogeneity are both improved. This phenomenon is attributed to BHCl2 depletion between the NH3 entry point and the hot deposition area, leading to the disappearance of reaction path N°2 in favour of reaction path N°1. The absence of BHCl2 at the reactor outlet indicates that its consumption through BN deposition can be fast and total even when the high standard total gas flow rate is applied. The results obtained by switching the gas entrances confirm the role of BHCl2 in the disorganization of the material structure and the deposition rate level. Indeed, with hydrogen dilution, keeping as long as possible BCl3 separated from H2 prevents the pre-reaction leading to BHCl2. The resulting kinetics and structure are then similar to those obtained with argon dilution. The hypothesis that can be drawn is that the reaction path N°1 involving Cl2BNH2 leads to highly crystallized BN whereas reaction path N°2 with BHCl2 produces poorly organized coatings.

The reduction of the degree of crystallization observed when H2 is the diluent gas and with the CVD device in standard configuration may originate from the growth of quasi-amorphous free boron. These boron clusters could impede the growth of the highly organized domains like in the case of boronrich pyrocarbon materials [START_REF] Jacques | LPCVD and characterization of boron-containing pyrocarbon materials[END_REF]. For the BN deposition from BCl3-NH3-H2 and in conditions similar to ours, the deposit was found to be a mixture of hexagonal BN and elemental boron when α ≤ 1 [START_REF] Hannache | Boron nitride chemical vapour infiltration of fibrous materials from BCl3-NH3-H2 or BF3-NH3 mixtures: A thermodynamic and experimental approach[END_REF] [START_REF] Huang | Investigation of the BN films prepared by low pressure chemical vapor deposition[END_REF]. But, as in the present work α was always greater than one and B-B bonds were not detected by XPS, BHCl2 is unlikely to lead to such boron-rich parts. Instead, the poorly crystallized domains resulting from reaction path N°2 have a boron-to-nitrogen ratio close to one. A most likely hypothesis would be the incorporation of hydrogen in the coating interfering with its structural organization. Hydrogen is indeed a by-product of the last reaction occurring at the substrate surface according to path N°2. A parallel can be drawn with laminar pyrocarbon deposition. It has been shown from elastic recoil detection analysis (ERDA) that the microtexture of pyrocarbon and the residual hydrogen trapped in the coating (which is dependent on homogeneous and heterogeneous dehydrogenations) are both correlated [START_REF] Lavenac | Deposition process of laminar pyrocarbon from propane[END_REF] [47] [START_REF] Weisbecker | Microstructure of pyrocarbons from pair distribution function analysis using neutron diffraction[END_REF]. The measurement of the hydrogen content in the different BN coatings should be useful, in a further work, for verifying this hypothesis. For BN infiltration purpose, it would be also interesting to study the effects of the internal surface area using different porous substrates. This parameter was indeed found to be very influent on the deposition chemistry for other chemical systems [START_REF] Hüttinger | Chemistry and kinetics of chemical vapor infiltration of pyrocarbon -VI. Mechanical and structural properties of infiltrated carbon fiber felt[END_REF]. Since BCl3-NH3-H2 mixtures were shown to be unsuitable for the deposition of well crystallized hexagonal BN within porous substrates [START_REF] Hannache | Boron nitride chemical vapour infiltration of fibrous materials from BCl3-NH3-H2 or BF3-NH3 mixtures: A thermodynamic and experimental approach[END_REF], such a study should be performed with another carrier gas than hydrogen.

Conclusion

The effects of the deposition temperature and total gas flow rate on the microstructure of BN coatings deposited from BCl3-NH3-H2 at low pressure have been studied. For two given deposition parameter sets, a comparison with the BCl3-NH3-Ar system has shown that the coatings deposited with Ar exhibit a higher crystallization degree and a better structural homogeneity than those deposited with H2. Ex situ FTIR analyses of the exhaust gases, coupled with ab initio vibrational mode calculations, have allowed assigning particular peaks of the spectrum to vibrational bands to aminodichloroborane (Cl2BNH2). The changes in the Cl2BNH2 concentration in the residual gases as a function of deposition temperature, the gas flow rate and the growth kinetics, have shown that this species can be considered either as an intermediate or an effective precursor of highly crystallized BN domains, whether H2 or Ar is used as a carrier gas. The BCl3-H2 gas mixture has also been studied by FTIR. BHCl2 is formed even at temperature as low as 500 °C. BHCl2 seems to be another intermediate species, which can react with NH3 to produce BN. The resulting material consists of poorly organized domains disorganizing the overall material structure. BN interphases with a high degree of crystallinity combined with a good structural homogeneity may be favourable to the oxidation resistance of CMCs during their use in severe environments. One way to deposit such interphases from the conventional BCl3-NH3 system is to avoid either the use of H2 or the direct reaction between H2 and BCl3 by optimizing the injection of the different gases into the CVD reactor. Tables Table 1. Growth rates (± 0.1 µm/h) and η factor values for BN coatings deposited from BCl3-NH3-H2 gas mixtures at different temperatures T and for different total gas flow rates Qtot. BN (s ) + 2HCl (g) + H 2 (g)

Qtot

Figure 2 -Figure 3 -Figure 4 -Figure 5 -Figure 7 -Figure 8 - 2 Figure 9 -Figure 10 -Figure 11 -Figure 12 -

 23457829101112 Figure 2 -Typical asymmetry of the XRD peak related to the diffraction from adjacent basal planes of deposited sp 2 -BN

Table 2 .

 2 Average binding energies and proportions of B 1s components measured by XPS for BN films deposited from BCl3-NH3-H2 gas mixtures with Qtot = 360 sccm and at 1200 °C

	(sccm)	100	200	242	300	360	360	360	360	360	360
	T (°C)	1200 1200 1200 1200	900	1000 1100 1200 1300 1400
	Growth rate (µm/h)	1.4	2.9	3.1	3.5	0.7	1.3	2.1	3.5	4.4	5.3
	η	0.6	0.5	0.5	0.5	0.7	0.5	0.5	0.4	0.3	0.3
				Component Energy (eV) % B-N 190.8 79 B-NO 191.9 13 B-CO 189.7 6 B-C 188.6 2

Table 3 .

 3 IR vibrational modes and relative intensities calculated for Cl2BNH2. δ and ν refer to as bending and stretching vibrations, respectively and the subscripts a and s refer to as asymmetric and symmetric modes, respectively

	Mode Position (cm -1 ) Relative intensity (a.u.)	νa(NH2) 3697 42	νs(NH2) 3596 60	90%δ(NH2) + 10%ν(BN) 1624.4 169	77%ν(BN) + 10%δ(NH2) + 13%νs(BCl2) 1347.6 166	75%δ(BNH) + 25%δ(NBCl) 1073.3 274	73%νa(BCl2) + 27%δ(BNH) 768.5 98	86%νs(BCl2) + 14%ν(BN) 549.3 17
	Table 4. FTIR peak areas for residual BCl3 and Cl2BNH2 from BCl3-NH3-H2 and BCl3-NH3-Ar gas mixtures (T = 1200 °C, Qtot = 200 sccm)
	Diluent gas BCl3 peak area (a.u.) Unreacted BCl3 (%) Cl2BNH2 peak area (a.u.) H2 0.13 (± 0.01) 3 0.17 (± 0.01) Ar 0.16 (± 0.01) 4 0.16 (± 0.01)

Figures

Figure 1 -LPCVD reactor in standard configuration and FTIR gas phase analysis apparatus

Acknowledgements

This work was supported by SAFRAN CERAMICS through a grant given to P. Carminati. The authors would like to thank L. Lapuyade from LCTS and C. Labrugère from PLACAMAT (UMS 3626 CNRS-Bordeaux University), for XPS analysis and data treatment. The authors are indebted to B. Cossou who participated to the deposition of some BN coatings. Finally, the authors wish to pay tribute to the late E. Buet and express their gratitude to his colleague A. Delcamp from SAFRAN CERAMICS for fruitful discussions.


Diana Lucia

Farfan Cabrera

Nicolas Gogin

David Morland

Dimitri Papathanassiou

Nicolas Passat

Segmentation of axillary lymph nodes in PET/CT scans: First experiments

The analysis of axillary lymph nodes is of crucial importance for the staging of breast cancer. As a consequence, an accurate segmentation of the nodes reached by cancer can constitute a precious help for computer-aided diagnosis. However, due to the size of axillary lymph nodes in PET/CT images, and to the low resolution of PET data where their abnomal metabolic hyperactivity may be observed, segmentation remains a challenging task. We investigate the relevance of considering axillary lymph nodes segmentation from PET/CT images, based on Convolutional Neural Networks (CNNs). To this end, our initial working hypotheses were twofold: first, taking advantage of both anatomical information from CT, for detecting the nodes, and from functional information from PET for detecting the inflammatory ones; second, considering region-based attributes extracted from component-tree analysis of PET images in order to enrich the information natively carried by PET, with features that can hardly be inferred by CNNs directly from the images. We describe our first results, and discuss about the validity of these working hypotheses.

Introduction

Breast cancer is one of the most common diseases in women and one of the principal causes of death in females. Approximately 1.38 million cases are detected worldwide per year and as a consequence causes 458,000 deaths. This type of cancer develops from breast tissue; lymph nodes near these regions are then among the first structures to be affected. This motivates the involvement of lymph nodes in the usual TNM protocol dedicated to the staging of breast, that relies on three criteria: size of tumor (T); number of lymph nodes reached by cancer (N); and metastasis state (M).

Positron Emission Tomography (PET), generally coupled with X-ray Computed Tomography (CT) is widely used for imaging purpose in cancer, and in particular in the case of breast cancer [START_REF] Vercher-Conejero | Positron emission tomography in breast cancer[END_REF][START_REF] Krammer | 18 F-FDG PET/CT for initial staging in breast cancer patients-Is there a relevant impact on treatment planning compared to conventional staging modalities[END_REF][START_REF] Kaseda | Identification of false-negative and false-positive diagnoses of lymph node metastases in non-small cell lung cancer patients staged by integrated 18F-FDG-positron emission tomography/computed tomography: A retrospective cohort study[END_REF][START_REF] Piva | Comparative diagnostic accuracy of 18F-FDG PET/CT for breast cancer recurrence[END_REF]. Whereas PET provides information on the high metabolism of cancerous cells, CT provides anatomical information on the structures of interest, with a high spatial resolution. However, it was observed by [START_REF] Groheux | 18F-FDG PET/CT for staging and restaging of breast cancer[END_REF] that PET/CT data experiment two major limitations. First, patients in early stages of cancer may have a very small quantity of cancerous cells. In this context, PET/CT may not easily allow to detect these few cells. Second, as inflammatory cells have a metabolism similar to cancerous cells, the putative presence of such cells may lead to false positives.

Despite these difficulties, PET/CT data constitute an important source of information that may be used for computer-aided diagnosis in the case of breast cancer. The challenging properties of these bimodal images (low resolution of PET, possible presence of false positives) also argue in favour of developing robust lymph node segmentation methods.

However, the literature specifically dedicated to lymph node segmentation is still rather limited. In this context, Deep Learning (DL) has recently emerged as a promising segmentation paradigm [START_REF] Ehteshami Bejnordi | Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer[END_REF], that seems to outperform other standard machine learning approaches for this specific task. In particular, it was shown by [START_REF] Wang | Comparison of machine learning methods for classifying mediastinal lymph node metastasis of non-small cell lung cancer from 18 F-FDG PET/CT images[END_REF] that Convolutional Neural Networks (CNNs) [START_REF] Long | Fully convolutional networks for semantic segmentation[END_REF], already used for PET/CT co-segmentation by [START_REF] Zhong | 3D fully convolutional networks for co-segmentation of tumors on PET-CT images[END_REF], is a potentially relevant paradigm.

A second, recent approach dedicated to PET/CT analysis consists of considering hierarchical image models in order to emphasize the mixed spatial-spectral information carried by PET data. In this context, some morphological trees, and in particular the component-tree [START_REF] Salembier | Antiextensive connected operators for image and sequence processing[END_REF], have been involved in segmentation methods, e.g. for interactive PET segmentation [START_REF] Grossiord | Hierarchies and shape-space for PET image segmentation[END_REF], lymphoma lesion segmentation from PET/CT [START_REF] Grossiord | Automated 3D lymphoma lesion segmentation from PET/CT characteristics[END_REF], or coupled PET/enhanced CT co-segmentation [START_REF] Alvarez Padilla | Hierarchical forest attributes for multimodal tumor segmentation on FDG-PET/contrast-enhanced CT[END_REF]. These methods rely on the hypothesis that hierarchical image models constitute an efficient data-structure for extracting high-level, region-based features that can be hardly computed by other strategies [START_REF] Machairas | New general features based on superpixels for image segmentation learning[END_REF][START_REF] Conze | Scale-adaptive supervoxel-based random forests for liver tumor segmentation in dynamic contrast-enhanced CT scans[END_REF].

Our initial purpose was to consider jointly both approaches, namely CNNs and hierarchical image models, in order to develop a lymph node automatic segmentation method that will take advantage not only of the complementary information carried by PET and CT, but also of highlevel features that could not be implicitly discovered from the native images by deep-learning architectures. We present our methodology, and experimental results that shed light on the successes and failures of the proposed approach, and emphasize the next steps and challenges to be tackled in our work.

CNN architecture

Our proposed CNN is based on the U-Net architecture [START_REF] Ronneberger | U-Net: Convolutional networks for biomedical image segmentation[END_REF]; see Figure 1. The first 3 layers act as an encoder; they perform volume downsampling that correspond to the CNN feature extraction. The last 3 layers act, symetrically, as a decoder; they perform volume up-sampling. During this up-sampling, some skip connections issued from the input PET image provide information for the output volume reconstruction. The loss function is the Dice score whereas the used optimizer is Nadam [START_REF] Dozat | Incorporating Nesterov momentum into Adam[END_REF].

This architecture is designed for considering multiple inputs, by duplicating the encoder part for each of these inputs. Basically, it uses two inputs, namely the PET image and its associated CT image. Indeed, cancer lymph nodes are structures with a globally round shape, which are perceived in PET as high-intensity, compact structures. However, other tissues and organs with round shape can present a high metabolic activity in PET, thus leading to possible false positives segmentation. In order to discriminate both kinds of structures, nuclear medicine FIG. 1 -The CNN architecture, illustrated here for two inputs, namely the PET and CT images.

doctors generally identify cancer lymph nodes by observing both PET and CT data. This is a strategy we chose to reproduce in our CNN, in order to also take into account morphological information in addition to functional one.

Our working hypothesis is that augmenting the information provided as input should improve the segmentation efficiency of the CNN, compared to using the PET data only. This motivates the addition of the CT data. More generally, this also justifies our strategy of computing region-based features from these data, in order to build feature maps involved as supplementary inputs.

Data

Our data are composed of 52 PET/CT full-body scans coming from 52 patients with different breast cancer stages. These data may have different resolutions. For instance, 4 of them were obtained with a scanner purchased before 2015, thus resulting in lower resolutions compared to the other images. In order to homogeneize the data, all exams were preprocessed in order to obtain isotropic resolution of 1 mm 3 . Since they are acquired during the same exam, the PET and CT volumes were assumed registered, so that one voxel in the CT volume should correspond to the same voxel in the PET volume.

After normalization, each exam contains millions of voxels (e.g. 500×500×800 volumes). This implies a high cost in terms of both memory and computational resources. In order to reduce this cost, thresholding-based lung segmentation was performed in order to extract the axillary region of interest (ROI). Beyond cost reduction, this also allows one to avoid false positives that may be generated within other parts of the body. Figure 2 illustrates this extraction of the axillary ROI.

We trained our model with 320 lymph nodes of CT full body scans (from neck to coccyx) from these 52 patients' images. Initially, we considered to work with both pathological and non-pathological lymph nodes. As a consequence, the morphology of these nodes may be different. Indeed, most lymph nodes that contain cells with tumors tend to have a larger volume, and an ellipsoidal morphologically. By contrast, healthy nodes tend to present a "bean" shape, and they are smaller. Figure 3 illustrates the difference between a node that contains tumour cells versus a node that does not.

Component-tree-based feature extraction

The component-tree is a lossless hierarchical model dedicated to grey-level images. Basically, a component-tree is a rooted, connected, acyclic graph (i.e. a tree) where each node corresponds to a connected component of a binary level-set of the image. These nodes / connected components are organized with respect to the inclusion relation.

When considering the ≤ relation on grey-level values of the image, the component-tree is also called max-tree. In such case, the root of the tree corresponds to the level-set at the lowest value (i.e. 0) where the unique connected component is the whole image support. At the other side of the max-tree, i.e. at the extremities of the branches, the leaves correspond to the flat zones of locally maximal values. In the case of PET images, these regions correspond to high-metabolism areas.

The max-tree can be used as a data-structure allowing to compute features for each node / connected component [START_REF] Breen | Attribute openings, thinnings, and granulometries[END_REF]. More precisely, our purpose is to compute for each relevant node of the max-tree of the PET image, some feature values that gather high-level information that are not directly available to CNNs.

Node feature extraction

Let us assume that we have computed the max-tree of the considered PET image. For each node, we aim to compute two specific features: (1) the volume; and (2) the compacity FIG. 3 -A pathological lymph node next to 3 non-pathological ones (axial view). [START_REF] Grossiord | Hierarchies and shape-space for PET image segmentation[END_REF]. Indeed, the lesions are of low volume (between 5 and 40 mm 3 ) and rather compact (round shape).

The volume (V ) is proportional to the number of voxels in the connected component of the processed node.

The compacity (C) is more complex to compute, in particular in a Cartesian grid of dimension 3, where the size of a digital boundary of dimension 2 is not defined in a well-posed way. We chose to approximate the compacity by computing the bounding box of the connected component, and by considering as compact an object with a bounding box close to a cube (i.e. with its height, width and depth globally equal). This measure, although not exact, constitutes a fair approximation of compacity, in particular when dealing with spherical targets.

For each node, the two feature values V and C are computed. For the nodes of relevant volume V (i.e. between 5 and 40 mm 3 ) we associate the node to its actual compacity. The other, over/undersized, nodes are assigned a negative value that means that the feature / the node is non-relevant.

Feature map construction

Each node of the max-tree of the PET image is then associated with two feature values V and C. However, CNNs consist of performing convolutions with 3D kernels acting on 3D data. This is not the case of a max-tree, which is organized as a dimension-less graph structure. It is then mandatory to embed the feature values computed at the nodes in a feature map defined the same way as the PET image, i.e. in a 3D Cartesian grid.

A voxel of the PET image belongs, in general, to many nodes of the max-tree. Consequently, for a given voxel, many feature values are available for V and C. In particular, it is required to choose, for each voxel, the "most relevant" feature values between the candidate nodes where it lies.

Then, for any voxel x, we study the evolution of the value V for all the nodes from the node of maximal value containing x, until the root node. We search the first strong gradient on V between two successive nodes. It occurs when the current branch is fused with others, and/or when other regions of different semantics merge with the current region containing x. When such gradient is detected, we choose as feature values for x the values V and C of the last node before the gradient occurs.

These feature maps finally computed can then be considered as input of the CNN, for both learning and segmentation.

Segmentation results

We trained on 640 patches (320 patches containing lymph nodes and 320 patches containing other structures within the axillary region). The initial learning rate was set to 0.0001 and the number of epochs was 125.

Figure 4 shows the loss function evolution during the training. The loss function value on the validation set converges near 0.6, whereas the loss function value on the training set converges near 0.5.

Figure 5 illustrates segmentation results on 6 different exams from the validation set. One can observe in cases (d-f) that our CNN model is able to distinguish the region that is below the armpits from the rest of the axillary region. However, segmentation results are still not sufficiently accurate when it comes to predicting the contours of the lymph nodes. A possible reason to this fact is that lymph nodes are attached to the lymphatic vessels, and both have the same intensity. It is then difficult, even for medical experts, to correctly delineate the boundary between a lymph node and the lymphatic vessel to which it is connected.

In cases (a-c) we can observe an over-segmentation; larger structures near the heart are segmented in addition to lymph nodes. This over-segmentation influences the Dice score. These segmentation errors can be explained by the fact that the region near the heart tends to be hyperfixating in PET images. In addition, small, round structures around the heart which have a morphology similar to that of the lymph nodes appear to be inflamed or contain cancer cells in several exams. In such cases, using max-tree information could be valuable. Indeed, descriptive features such as lymph node area or lymph node morphology, obtained from the max-tree, could help to discriminate connected components corresponding to such false positives.

On the other hand, our model only relies on 360 examples of lymph nodes. In order to improve the results, it will be mandatory to increase our training set. Data augmentation techniques may contribute to such enrichment of the pool of information available for learning purpose. Nevertheless, additional real examples are also of crucial importance in order to enrich the variability of the training set.

Discussion

Lymph node clusters

In rare cases, we can observe that patients may contain several lymph nodes visually connected together, due to their small size and close relative positions, see Figure 6. In such cases, FIG. 6 -Lymph nodes, forming a cluster that visually appears as a large, single node. PET image, coronal view. medical experts consider these clusters as single nodes, since it is impossible for them to discriminate the lymph nodes composition within the clusters. In particular, it is then impossible to determine exactly how many lymph nodes are connected.

Considering these clusters in our training set, and assimilating them as single nodes, may lead to introduce inconsistency into the training process. Indeed these clusters are significantly different from single nodes, both in terms of size and morphology. These cases are then challenging to predict, since they appear as outliers (both in training and testing), compared to usual lymph nodes.

Registration issues between PET and CT volumes

Both CT and PET images are computed, slice by slice, during a same acquisition. However, the time required for both is quite different, from a few seconds for the CT, to several minutes for the PET. In such conditions, two kinds of movements can alter the PET image acquisition (whereas CT remains robust to such issues). First, breathing has an impact on the position of the axillary lymph nodes, which are located close to the lungs. An acquisition of several minutes will be altered by these physiological artifacts, leading to partial volume effects and/or displacement of the putative position of the nodes in the image. On the other hand, the patient is asked to have his/her arms stretched upwards. This position can rapidly become uncomfortable, leading the patient to slightly move. In such case, the spatial coherence of the lymph nodes between the beginning and the end of the PET image acquisition may be altered.

As a consequence, a same lymph node in the CT image may be located a few millimeters away (and blurred) in the PET image, as illustrated in Figure 7.

In our initial approach, the ground-truths for the lymph nodes contours were defined from the CT image, taking advantage of the accurate morphological information provided by these images. Unfortunately, the movement-based registration issues make this strategy non-valid, since we have no sufficient guarantee of spatial coherence between the lymph node position in the CT and the PET.

A potential solution to tackle this issue may consist of considering multimodal, non-rigid registration procedures. However, such approaches are designed to compute 3D continuous mappings between two images, whereas in our case, the spatial incoherence is related to complex 3D + time movements that cannot be modeled by such kinds of transformations. As a conclusion, it will then be mandatory to define further ground-truth directly from the PET im- ages (and no longer from CT ones). This will induce another difficulty, that lies in the fact that such functional images do not provide crisp frontiers between the nodes and their neighbourhood.

Perspective works

Segmentation of lymph nodes in PET/CT images is challenging, especially because these structures are small, sparse and located near the lungs. In our future work, we aim at segmenting tumors using two types of Neural Network architectures using different types of inputs:

(1) only gray-level information from PET; (2) only gray-level information from PET/CT; (3) gray-level information from the PET/CT combined with max tree descriptors.

It is important to keep in mind that PET and CT modalities can both bring information, which are indeed complementary. As a consequence, during training using both PET and CT information, it will be important to provide patches in PET and CT, whereas ground-truth mask will correspond to the PET contours only.

In addition, it will be also mandatory to increase both the precision of the segmentation, but also to determine a set of ground-truths sufficiently large, involving at least 1,000 different lymph nodes, in order to reach a sufficient amount of data for further avoiding over-fitting.

FIG. 2 -

 2 FIG. 2 -From left to right: original volume; mask of the segmented lungs; extraction of the axilary ROI (coronal view).

FIG. 4 -

 4 FIG. 4 -Loss function after 125 epochs. The orange slope corresponds to the training set loss function whereas the blue slope corresponds to the validation set loss function.

FIG. 5 -

 5 FIG. 5 -Predictions results on 6 different patients (maximum intensity projection, coronal view, axillary region). First column: ground-truth. Second column: lymph node segmentation results. Third column: comparison of ground-truth contours (in red) and segmentation contours (in yellow). Fourth column: Dice score (over 100) of each segmentation result.

FIG. 7 -

 7 FIG. 7 -Left: contouring of 2 lymph nodes in CT axial view. Right: Contouring of the same 2 lymph nodes in PET axial view. (See text.)

Acknowledgements

The research leading to these results has been supported by the French Association Nationale Recherche Technologie (ANRT).