Segmentation d'image échographique par minimisation de la complexité stochastique en vue du diagnostic sénologique.

L'objectif de cette thèse est de proposer et d'étudier une méthode de segmentation qui soit adaptée à l'imagerie échographique ultrasonore (US) et qui tienne compte de certaines contraintes rencontrées en milieu clinique. De ce fait, cette méthode se doit d'être robuste au bruit de speckle et à l'atténuation des ondes US dans le milieu, mais aussi rapide et ne nécessiter que peu, voire aucun paramètre à régler par l'opérateur. Dans ce cadre, les solutions fondées sur des contours actifs fondés sur la Minimisation de la Complexité Stochastique ont été étudiées. L'impact de différentes modélisations du speckle sur les résultats de ces techniques de segmentation a été caractérisé. Il a été montré qu'il est important de prendre en compte les variations de l'intensité moyenne du speckle induites par l'atténuation dans chaque région de l'image, à la fois pour la segmentation et pour l'analyse des propriétés du speckle. De plus, une stratégie hiérarchique de segmentation a été développée. Celle-ci permet notamment d'accroître la qualité des segmentations et de diminuer les temps de calcul.Les algorithmes de segmentation considérés étaient initialement conçus pour des formes polygonales peu adaptées à celles rencontrées dans le cadre d'applications médicales. Nous avons donc développé un nouveau modèle de contour fondé sur la théorie de l'information qui permet toujours une mise en oeuvre rapide des algorithmes et ne dépend d'aucun paramètre à régler par l'utilisateur. Testé sur des images synthétiques et réelles de fantômes échographiques, ce nouveau modèle permet de mieux décrire les formes régulières et arrondies des objets rencontrés en imagerie échographique.The purpose of this PhD thesis is to propose and study a segmentation method adapted to echographic ultrasound imaging that could be clinically operational (i.e. fast and parameter-free) and robust to both the speckle noise and the attenuation of the ultrasonic signal in the medium. The solutions we studied rely on statistical active contour methods that are based on the Minimization of the Stochastic Complexity (MSC). The impact on the segmentation results of several speckle noise models that still lead to fast segmentation algorithms has been characterized. A key feature of these models, that appears to be crucial for both the segmentation and the speckle characterization, is the ability to take into account the spatial variation of the average intensity induced by the attenuation of the signal in the medium. In addition, we proposed a hierarchical optimization strategy that improves segmentation results and decreases the computation time.Finally, a novel contour model that is adapted to smooth boundaries that are met in medical imaging is also proposed for the considered MSC segmentation algorithms. The construction of this contour model relies on Information Theory concepts. It still allows one to get low computation times and does not contain any tuning parameter. Evaluations performed on synthetic images and real echographic phantom images indicate that this contour model provides better segmentation results for smooth inclusions that usually compose the echographic images

Segmentation d'image échographique par minimisation de la complexité stochastique en vue du diagnostic sénologique.

L'objectif de cette thèse est de proposer et d'étudier une méthode de segmentation qui soit adaptée à l'imagerie échographique ultrasonore (US) et qui tienne compte de certaines contraintes rencontrées en milieu clinique. De ce fait, cette méthode se doit d'être robuste au bruit de speckle et à l'atténuation des ondes US dans le milieu, mais aussi rapide et ne nécessiter que peu, voire aucun paramètre à régler par l'opérateur. Dans ce cadre, les solutions fondées sur des contours actifs fondés sur la Minimisation de la Complexité Stochastique ont été étudiées. L'impact de différentes modélisations du speckle sur les résultats de ces techniques de segmentation a été caractérisé. Il a été montré qu'il est important de prendre en compte les variations de l'intensité moyenne du speckle induites par l'atténuation dans chaque région de l'image, à la fois pour la segmentation et pour l'analyse des propriétés du speckle. De plus, une stratégie hiérarchique de segmentation a été développée. Celle-ci permet notamment d'accroître la qualité des segmentations et de diminuer les temps de calcul.Les algorithmes de segmentation considérés étaient initialement conçus pour des formes polygonales peu adaptées à celles rencontrées dans le cadre d'applications médicales. Nous avons donc développé un nouveau modèle de contour fondé sur la théorie de l'information qui permet toujours une mise en oeuvre rapide des algorithmes et ne dépend d'aucun paramètre à régler par l'utilisateur. Testé sur des images synthétiques et réelles de fantômes échographiques, ce nouveau modèle permet de mieux décrire les formes régulières et arrondies des objets rencontrés en imagerie échographique.The purpose of this PhD thesis is to propose and study a segmentation method adapted to echographic ultrasound imaging that could be clinically operational (i.e. fast and parameter-free) and robust to both the speckle noise and the attenuation of the ultrasonic signal in the medium. The solutions we studied rely on statistical active contour methods that are based on the Minimization of the Stochastic Complexity (MSC). The impact on the segmentation results of several speckle noise models that still lead to fast segmentation algorithms has been characterized. A key feature of these models, that appears to be crucial for both the segmentation and the speckle characterization, is the ability to take into account the spatial variation of the average intensity induced by the attenuation of the signal in the medium. In addition, we proposed a hierarchical optimization strategy that improves segmentation results and decreases the computation time.Finally, a novel contour model that is adapted to smooth boundaries that are met in medical imaging is also proposed for the considered MSC segmentation algorithms. The construction of this contour model relies on Information Theory concepts. It still allows one to get low computation times and does not contain any tuning parameter. Evaluations performed on synthetic images and real echographic phantom images indicate that this contour model provides better segmentation results for smooth inclusions that usually compose the echographic images.AIX-MARSEILLE3-Bib. élec. (130559903) / SudocSudocFranceF

Smooth contour coding with minimal description length active grid segmentation techniques

International audienceWe analyze the influence of the contour coding term in segmentation techniques based on active grids and on the minimum description length (MDL) principle. These segmentation techniques have been developed up to now with a contour coding term adapted to polygonal objects. However, this approach can lead to degraded segmentation results for smooth contours of objects which can be observed for example in geoscience, medicine or microscopy. We demonstrate that an appropriate choice of the contour coding term can improve segmentation results with MDL active grid approaches in the presence of regions with smooth boundaries. This improvement opens a large class of application domains and still allows one to obtain low computational time

Une revue de quelques applications de la minimisation de la complexité stochastique pour la segmentation d'images par grille active

National audienc

Exploring uranium minor isotopes (U-233, U-236) as a new tracer to highlight uranium contamination downstream former uranium mine sites

International audienceUranium (U) is naturally occurring in the environment and its concentration ranges between 1 to 10 mg.kg-1 in the earth’s crust. In the vicinity of former uranium mines, these concentrations can increase by several orders of magnitude, due to U remobilisation from mill tailings and waste rocks. Potential runoff and erosion after the rehabilitation of the mining sites could therefore explain this increase of U in the surrounding lands, watercourses and wetlands. However, high U concentrations have already been observed in sediments and soils in areas not influenced by U mining activities. In fact, organic matter and reducing conditions in sediments and soils can lead to an important U accumulation originating from the geochemical background. Therefore, identifying U origin (mine versus geochemical background) in the vicinity of former U mines is a key element for contribution to the assessment of uranium mining waste management strategies. Natural processes like the alpha recoil effect and isotope fractionation limit the use of 234U/238U and 235U/238U isotope ratios as fingerprints to identify the U origin. In this work, the use of natural U minor isotopes was explored. The 236U/238U ratio of the geochemical background is estimated to be around 10-14. On the contrary, in U ore, the higher neutron flux from (α, n) reactions leads to a significant production of 236U by activation of 235U. Consequently, uranium ores show distinct isotope signatures with typical 236U/238U isotope ratios ranging between 10-12 and 10-10. However, 236U has also been released in the environment by global fallout from atmospheric nuclear weapon tests in the 1960s. This anthropogenic input of 236U in the environment increased the 236U/238U ratio of the geochemical background at levels close to U ore signature, thus limiting the use of this ratio as a fingerprint. Furthermore, natural 238U concentration variations can also induce fluctuation of the 236U/238U isotope ratios. In order to overcome these limitations, we investigated the use of environmental 233U, for which detection became possible only recently. In nature, the main production process of 233U is by neutron activation of 232Th. In the geochemical background, the resultant concentration of 233U is very low. In various U ores, measurements showed 233U/236U isotope ratios 10-4. The main origin of 233U in the environment is global fallout from the atmospheric nuclear weapon tests with a typical 233U/236U isotope ratio of 10-2 (Hain et al., 2017) produced fusion neutrons via 235U(n,3n)233U. This isotopic “contrast” between global fallout, the geochemical background and U ores makes the 233U/236U ratio a potential fingerprint to highlight U contamination of the environment by mining and milling activities.Measurements of 233U/236U ratios were performed by Accelerator Mass Spectrometry (AMS) at the Vienna Environmental Research Accelerator (VERA). First results of 233U/236U ratios in U ore samples, contaminated sediments from wetlands draining the former mine facilities and non-contaminated samples representing the geochemical background will be presented and discussed in this talk

Exploring uranium minor isotopes (U-233, U-236) as a new tracer to highlight uranium contamination downstream former uranium mine sites

International audienceUranium (U) is naturally occurring in the environment and its concentration ranges between 1 to 10 mg.kg-1 in the earth’s crust. In the vicinity of former uranium mines, these concentrations can increase by several orders of magnitude, due to U remobilisation from mill tailings and waste rocks. Potential runoff and erosion after the rehabilitation of the mining sites could therefore explain this increase of U in the surrounding lands, watercourses and wetlands. However, high U concentrations have already been observed in sediments and soils in areas not influenced by U mining activities. In fact, organic matter and reducing conditions in sediments and soils can lead to an important U accumulation originating from the geochemical background. Therefore, identifying U origin (mine versus geochemical background) in the vicinity of former U mines is a key element for contribution to the assessment of uranium mining waste management strategies. Natural processes like the alpha recoil effect and isotope fractionation limit the use of 234U/238U and 235U/238U isotope ratios as fingerprints to identify the U origin. In this work, the use of natural U minor isotopes was explored. The 236U/238U ratio of the geochemical background is estimated to be around 10-14. On the contrary, in U ore, the higher neutron flux from (α, n) reactions leads to a significant production of 236U by activation of 235U. Consequently, uranium ores show distinct isotope signatures with typical 236U/238U isotope ratios ranging between 10-12 and 10-10. However, 236U has also been released in the environment by global fallout from atmospheric nuclear weapon tests in the 1960s. This anthropogenic input of 236U in the environment increased the 236U/238U ratio of the geochemical background at levels close to U ore signature, thus limiting the use of this ratio as a fingerprint. Furthermore, natural 238U concentration variations can also induce fluctuation of the 236U/238U isotope ratios. In order to overcome these limitations, we investigated the use of environmental 233U, for which detection became possible only recently. In nature, the main production process of 233U is by neutron activation of 232Th. In the geochemical background, the resultant concentration of 233U is very low. In various U ores, measurements showed 233U/236U isotope ratios 10-4. The main origin of 233U in the environment is global fallout from the atmospheric nuclear weapon tests with a typical 233U/236U isotope ratio of 10-2 (Hain et al., 2017) produced fusion neutrons via 235U(n,3n)233U. This isotopic “contrast” between global fallout, the geochemical background and U ores makes the 233U/236U ratio a potential fingerprint to highlight U contamination of the environment by mining and milling activities.Measurements of 233U/236U ratios were performed by Accelerator Mass Spectrometry (AMS) at the Vienna Environmental Research Accelerator (VERA). First results of 233U/236U ratios in U ore samples, contaminated sediments from wetlands draining the former mine facilities and non-contaminated samples representing the geochemical background will be presented and discussed in this talk