Détection de contours des organes pelviens dans des images médicales par modèles de B-spline

A ce jour, en routine clinique, grâce aux technologies avancées d'imagerie par résonance magnétique (IRM), le diagnostic des troubles du système pelvien chez la femme dépend de l'analyse d'images IRM par les médecins avec un risque de subjectivités. La simulation éléments finis est un outil prometteur pour l'aide à la compréhension qui, entre autre basée sur l'IRM, peut réduire la subjectivité des analyses. Pour cela, nous introduisons une méthode permettant d'identifier semi-automatiquement les organes pelviens observables sur des images IRM. Ce travail permet de mettre en place des mesures objectives et quantitatives, qui aide à la modélisation géométrique du système pelvien et à l'analyse des mobilités pour les études plus approfondies. Un modèle paramétré de B-spline est utilisé comme descriptif de géométries dédiées. Ce modèle initial est recalé sur l'organe présenté dans l'image réelle par corrélation d'images virtuelles. Nous avons validé la détection (de la vessie, du vagin et du rectum) sur un jeu de données de 19 patientes, présentant des mobilités physiologiques ou pathologiques

Harmonization Across Imaging Locations(HAIL): One-Shot Learning for Brain MRI

For machine learning-based prognosis and diagnosis of rare diseases, such as pediatric brain tumors, it is necessary to gather medical imaging data from multiple clinical sites that may use different devices and protocols. Deep learning-driven harmonization of radiologic images relies on generative adversarial networks (GANs). However, GANs notoriously generate pseudo structures that do not exist in the original training data, a phenomenon known as "hallucination". To prevent hallucination in medical imaging, such as magnetic resonance images (MRI) of the brain, we propose a one-shot learning method where we utilize neural style transfer for harmonization. At test time, the method uses one image from a clinical site to generate an image that matches the intensity scale of the collaborating sites. Our approach combines learning a feature extractor, neural style transfer, and adaptive instance normalization. We further propose a novel strategy to evaluate the effectiveness of image harmonization approaches with evaluation metrics that both measure image style harmonization and assess the preservation of anatomical structures. Experimental results demonstrate the effectiveness of our method in preserving patient anatomy while adjusting the image intensities to a new clinical site. Our general harmonization model can be used on unseen data from new sites, making it a valuable tool for real-world medical applications and clinical trials.Comment: Under revie

Molecular Cloning and Characterization of an Acetylcholinesterase cDNA in the Brown Planthopper, Nilaparvata lugens

A full cDNA encoding an acetylcholinesterase (AChE, EC 3.1.1.7) was cloned and characterized from the brown planthopper, Nilaparvata lugens Stål (Hemiptera: Delphacidae). The complete cDNA (2467 bp) contains a 1938-bp open reading frame encoding 646 amino acid residues. The amino acid sequence of the AChE deduced from the cDNA consists of 30 residues for a putative signal peptide and 616 residues for the mature protein with a predicted molecular weight of 69,418. The three residues (Ser242, Glu371, and His485) that putatively form the catalytic triad and the six Cys that form intra-subunit disulfide bonds are completely conserved, and 10 out of the 14 aromatic residues lining the active site gorge of the AChE are also conserved. Northern blot analysis of poly(A)+ RNA showed an approximately 2.6-kb transcript, and Southern blot analysis revealed there likely was just a single copy of this gene in N. lugens. The deduced protein sequence is most similar to AChE of Nephotettix cincticeps with 83% amino acid identity. Phylogenetic analysis constructed with 45 AChEs from 30 species showed that the deduced N. lugens AChE formed a cluster with the other 8 insect AChE2s. Additionally, the hypervariable region and amino acids specific to insect AChE2 also existed in the AChE of N. lugens. The results revealed that the AChE cDNA cloned in this work belongs to insect AChE2 subgroup, which is orthologous to Drosophila AChE. Comparison of the AChEs between the susceptible and resistant strains revealed a point mutation, Gly185Ser, is likely responsible for the insensitivity of the AChE to methamidopho in the resistant strain

The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn)

Automated brain tumor segmentation methods have become well-established and reached performance levels offering clear clinical utility. These methods typically rely on four input magnetic resonance imaging (MRI) modalities: T1-weighted images with and without contrast enhancement, T2-weighted images, and FLAIR images. However, some sequences are often missing in clinical practice due to time constraints or image artifacts, such as patient motion. Consequently, the ability to substitute missing modalities and gain segmentation performance is highly desirable and necessary for the broader adoption of these algorithms in the clinical routine. In this work, we present the establishment of the Brain MR Image Synthesis Benchmark (BraSyn) in conjunction with the Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2023. The primary objective of this challenge is to evaluate image synthesis methods that can realistically generate missing MRI modalities when multiple available images are provided. The ultimate aim is to facilitate automated brain tumor segmentation pipelines. The image dataset used in the benchmark is diverse and multi-modal, created through collaboration with various hospitals and research institutions.Comment: Technical report of BraSy

The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)

Pediatric tumors of the central nervous system are the most common cause of cancer-related death in children. The five-year survival rate for high-grade gliomas in children is less than 20\%. Due to their rarity, the diagnosis of these entities is often delayed, their treatment is mainly based on historic treatment concepts, and clinical trials require multi-institutional collaborations. The MICCAI Brain Tumor Segmentation (BraTS) Challenge is a landmark community benchmark event with a successful history of 12 years of resource creation for the segmentation and analysis of adult glioma. Here we present the CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs 2023 challenge, which represents the first BraTS challenge focused on pediatric brain tumors with data acquired across multiple international consortia dedicated to pediatric neuro-oncology and clinical trials. The BraTS-PEDs 2023 challenge focuses on benchmarking the development of volumentric segmentation algorithms for pediatric brain glioma through standardized quantitative performance evaluation metrics utilized across the BraTS 2023 cluster of challenges. Models gaining knowledge from the BraTS-PEDs multi-parametric structural MRI (mpMRI) training data will be evaluated on separate validation and unseen test mpMRI dataof high-grade pediatric glioma. The CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs 2023 challenge brings together clinicians and AI/imaging scientists to lead to faster development of automated segmentation techniques that could benefit clinical trials, and ultimately the care of children with brain tumors

Evaluation of mobility and geometric modeling of female pelvic system by medical image analysis

Le meilleur traitement des troubles des mobilités du système pelvien féminin est un enjeu de société concernant particulièrement les femmes âgées. C'est dans ce contexte que cette thèse porte sur le développement des méthodes d'analyse d'images médicales permettant d'évaluer les mobilités pelviennes et modéliser les géométries des organes pelviens. Pour ce faire, nous proposons des solutions reposant sur le recalage des modèles déformables sur des images, issues de la technique d'Imagerie par Résonance Magnétique (IRM). L'ensemble des résultats permet, à partir d'IRM, spécifiquement à chaque patiente, de détecter la forme et de quantifier le mouvement d'une part des organes et de reconstruire leurs surfaces. Ce travail facilite la simulation du comportement des organes pelviens par la méthode des éléments finis. L'ensemble des outils développés a pour objectif d'aider à comprendre le mécanisme des pathologies. Ceci permettra enfin de mieux prédire l'apparition de certaines d'entre elles, de préciser et personnaliser les procédures chirurgicales.The better treatment of female pelvic mobility disorders has a social impact affecting particularly aged women. It is in this context that this thesis focuses on the development of methods in medical image analysis, for the evaluation of pelvic mobility and the geometric modeling of the pelvic organs. For this purpose, we provide solutions based on the registration of deformable models on Magnetic Resonance Images (MRI). All the results are able to detect the shape and quantify the movement of a part of the organs and to reconstruct their surfaces from patient-specific MRI. This work facilitates the simulation of the behavior of the pelvic organs using finite element method. The objective of these developed tools is to help to better understand the mechanism of the pathologies. They will finally allow to better predict the presence of certain diseases, as well as make surgical procedures more accurate and personalized

Reconstruction et complétion de maillages sous contraintes

Dans le cadre d'un projet visant la réalisation d'un simula-teur d'accouchement, nous cherchons à créer les modèles géométriques des organes impliqués à partir d'images médicales. Mais ces images médi-cales ne contiennent généralement qu'une partie significative de l'organe. Nous nous focalisons ainsi sur la reconstruction des maillages générés et la complétion des parties manquantes. Pour cela, nous avons étudié dif-férentes méthodes de modification et de complétion des maillages. Par rapport aux méthodes existantes, notre solution ne concerne pas seule-ment la complétion de maillages mais elle tient aussi compte de diffé-rentes contraintes pré-définies. Notre solution inclut la triangulation, le raffinement et la déformation sous contraintes des maillages surfaciques. Abstract In the context of the Childbirth Simulator Project, we need to create the geometric models of organs from medical imaging. In the general case, the medical images contain only a significant part of the organ, thus, our problem is how to reconstruct and complete the mesh by filling the missing parts. To achieve this goal,we have studied the main approaches for mesh editing and holes filling in order to offer our approach. Compared with the existing methods, our approach also take into account the various pre-defined constraints particularly during the mesh completion. Our method includes triangulation, refinement and constrained deformation of surface meshes

Use of Geographically Weighted Regression (GWR) to Reveal Spatially Varying Relationships between Cd Accumulation and Soil Properties at Field Scale

The spatial variation of correlation between Cd accumulation and its impact factors plays an important role in precise management of Cd contaminated farmland. Samples of topsoils (n = 247) were collected from suburban farmland located at the junction of the Yellow River Basin and the Huaihe River Basin in China using a 200 m × 200 m grid system. The total and available contents of Cd (T-Cd and A-Cd) in topsoils were analyzed by ICP-MS, and their spatial distribution was analyzed using kriging interpolation with the GIS technique. Geographically weighted regression (GWR) models were applied to explore the spatial variation and their influencing mechanisms of relationships between major environmental factors (pH, organic matter, available phosphorus (A-P)) and Cd accumulation. Spatial distribution showed that T-Cd, A-Cd and their influencing factors had obvious spatial variability, and high value areas primarily cluster near industrial agglomeration areas and irrigation canals. GWR analysis revealed that relationships between T-Cd, A-Cd and their environmental factors presented obvious spatial heterogeneity. Notably, there was a significant negative correlation between soil pH and T-Cd, A-Cd, but with the increase of pH in soil the correlation decreased. A novel finding of a positive correlation between OM and T-Cd, A-Cd was observed, but significant positive correlation only occurred in the high anthropogenic input area due to the complex effects of organic matter on Cd activity. The influence intensity of pH and OM on T-Cd and A-Cd increases under the strong influence of anthropogenic sources. Additionally, T-Cd and A-Cd were totally positively related to soil A-P, but mostly not significantly, which was attributed to the complexity of the available phosphorus source and the differences in Cd contents in chemical fertilizer. Furthermore, clay content might be an important factor affecting the correlation between Cd and soil properties, considering that the correlation between Cd and pH, SOM, A-P was significantly lower in areas with lower clay particles. This study suggested that GWR was an effective tool to reveal spatially varying relationships at field scale, which provided a new idea to further explore the related influencing factors on spatial distribution of contaminants and to realize precise management of a farmland environment