Bladder segmentation in MRI images using active region growing model.

International audienceProstate segmentation in MRI may be difficult at the interface with the bladder where the contrast is poor. Coupled-models that segment simultaneously both organs with non-overlapping constraints offer a good solution. As a pre-segmentation of the structures of interest is required, we propose in this paper a fast deformable model to segment the bladder. The combination of inflation and internal forces, locally adapted according to the gray levels, allow to deform the mesh toward the boundaries while overcoming the leakage issues that can occur at weak edges. The algorithm, evaluated on 33 MRI volumes from 5 different devices, has shown good performance providing a smooth and accurate surface

Intra subject 3D/3D Kidney Registration using Local Mutual Information Maximization

International audienceOne of the goal of the Nephron-Sparing Surgery properative planning is to delineate as exactly as possible the renal carcinoma and to specify its relations to the renal arterial, venous and collecting system anatomies. The classical preoperative imaging system is the Spiral CT Urography, which gives sucessive 3D acquisitions of complementary information The integration of this information within the a patient spacific anatomical referential can be achieved by intra-patient registration techniques. A local MI maximization registration method is proposed in this paper. The kidneys are extracted from the abdomen volumes and then the registration between the extracted kidneys is implemented by maximizing the MI between them. The experimental results demonstrates that this method is effective

CNN-based real-time 2D-3D deformable registration from a single X-ray projection

Purpose: The purpose of this paper is to present a method for real-time 2D-3D non-rigid registration using a single fluoroscopic image. Such a method can find applications in surgery, interventional radiology and radiotherapy. By estimating a three-dimensional displacement field from a 2D X-ray image, anatomical structures segmented in the preoperative scan can be projected onto the 2D image, thus providing a mixed reality view. Methods: A dataset composed of displacement fields and 2D projections of the anatomy is generated from the preoperative scan. From this dataset, a neural network is trained to recover the unknown 3D displacement field from a single projection image. Results: Our method is validated on lung 4D CT data at different stages of the lung deformation. The training is performed on a 3D CT using random (non domain-specific) diffeomorphic deformations, to which perturbations mimicking the pose uncertainty are added. The model achieves a mean TRE over a series of landmarks ranging from 2.3 to 5.5 mm depending on the amplitude of deformation. Conclusion: In this paper, a CNN-based method for real-time 2D-3D non-rigid registration is presented. This method is able to cope with pose estimation uncertainties, making it applicable to actual clinical scenarios, such as lung surgery, where the C-arm pose is planned before the intervention

Experimental Methodology for the Evaluation of the 3D Visualization of Quantitative Information: a Case Study Concerning SEEG Information

The visual analysis of Stereoeletroencephalographic (SEEG) signals in their anatomical context is aimed at understanding the spatio-temporal dynamics of epileptic processes. The magnitude of these signals may be encoded by graphical glyphs, having a direct impact on the perception of the values. This problem has motivated an evaluation of the quantitative visualization of these signals, specifically with regard to the influence of the coding scheme of the glyphs on the understanding and analysis of the signals. This work describes an experiment conducted with human observers in order to evaluate three different coding schemes used to visualize the magnitude of SEEG signals in their 3D anatomical context. Before the experiment we had no clue to which of these schemes would provide better performance to the human observers, while the literature offered theories supporting different answers. Through our experiment we intended to find out if any of these coding schemes allows better performance in two aspects: accuracy and speed. A protocol has been developed to measure these aspects. The results presented in this work were obtained from 40 human observers. Comparison between the three coding schemes was first performed through an Exploratory Data Analysis (EDA). Statistical significance of this comparison was then established using nonparametric methods. Influence of some other factors on the observers’ performance was also investigated

Adaptation and evaluation of the multiple organs OSD for T2 MRI prostate segmentation

International audienceThis paper deals with the adaptation, the tuning and the evaluation of the multiple organs Optimal Surface Detection (OSD) algorithm for the T2 MRI prostate segmentation. This algorithm is initialized by first surface approximations of the prostate (obtained after a model adjustment), the bladder (obtained automatically) and the rectum (interactive geometrical model). These three organs are then segmented together in a multiple organs OSD scheme which proposes a competition between the gray level characteristics and some topological and anatomical information of these three organs. This method has been evaluated on the MICCAI Grand Challenge: Prostate MR Image Segmentation (PROMISE) 2012 training dataset

GPU Accelerated High Intensity Ultrasound Acoustical Power Computation

International audienceThe simulation of the hepatocellular carcinoma therapy effects is often used for the intervention planning. As the physical-based model of the simulation is very time-consuming, the speed of this method becomes an obstacle during the clinical application simulation. In order to accelerate the simulation, a GPU-based (Graphic Processing Unit) acceleration method of the pressure field estimation is proposed in this paper. The results demonstrate that the proposed acceleration method can solve the time-consuming problem

Segmentation d'images scanner X du foie par Max-Flow/Min-Cut

Dans le contexte d'une application médicale spécifique, le traitement mini-invasif des cancers primitifs du foie par ultrasons à haute intensités, notre étude porte sur une méthode de segmentation 3D semi-automatique rapide qui permet d'isoler le foie et les différents réseaux vasculaires hépatiques à partir de volumes acquis en scanner X. Cette méthode est caractérisée par une description du volume sous la forme d'un graphe où les poids des liens entre noeuds décrivent soit des degrés de similarité entre voxels de la même classe (approche région), soit des degrés de discontinuité d'un voxel par rapport à un voisin (approche contours). Ces différents poids sont définis après une première phase d'apprentissage interactive. L'algorithme de Max-Flow/Min-Cut est ensuite utilisé pour partitionner le volume en deux sous-ensembles représentatifs des classes

Visualisation Scientifique en médecine.<br />Application à la visualisation de l'anatomie et à la visualisation en épileptologie clinique

En médecine, le rôle de l'image est primordial. Depuis la renaissance, l'image a été un des vecteurs principaux de la transmission du savoir. Plus récemment, l'essor des techniques d'imageries tridimensionnelles n'a fait qu'étendre l'importance de l'image à la plupart des disciplines et des procédures médicales. Tout naturellement donc, la médecine a représenté un des domaines d'application privilégiés de la visualisation scientifique. Mes travaux de recherche s'inscrivent directement dans cette discipline de la visualisation scientifique et se présentent sous la forme de solutions de représentations originales apportées et associées à certaines problématiques médicales.Pour cela, une réflexion sur l'outil de visualisation a été menée afin de proposer un cadre bien défini qui puisse guider l'élaboration d'un outil de représentation répondant à une discipline et à une problématique particulière. Le point le plus original de cette réflexion concerne un essai de formalisation de l'évaluation de la performance des outils de visualisation.Deux grands domaines d'application ont justement permis de démontrer la pertinence de ce cadre général de la visualisation :- La visualisation générale de l'anatomie avec, dans un premier temps, la conception d'un outil générique de visualisation de données médicale, le lancer de rayons multifonctions. Cet outil a été ensuite étendu selon deux axes de recherche, d'une part l'intégration de modèles de connaissances dans la procédure de synthèse d'images et d'autre part, l'imagerie interventionnelle et plus particulièrement des applications en urologie.- Les apports de la visualisation pour l'interprétation des données recueillies sur le patient épileptique et plus particulièrement l'élaboration d'outils complémentaires permettant une analyse progressive des mécanismes et structures impliqués dans la crise