Olivier Colot

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Accurate localization and contouring of prostate are crucial issues in prostate cancer diagnosis and/or therapies. Although several semi-automatic and automatic segmentation methods have been proposed, manual expert correction remains necessary. We introduce a new method for automatic 3D segmentation of the prostate gland from magnetic resonance imaging(More)
Anew fuzzy image filter controlled by interval-valued fuzzy sets (IVFS) is proposed for removing noise from images. The proposed approach is based on IVFS entropy application. IVFS makes it possible to take into account the total uncertainty inherent to image processing, and particularly noise removal is considered. Interval-valued fuzzy sets entropy is(More)
PURPOSE To investigate the performance of a new method of automatic segmentation of prostatic multispectral magnetic resonance images into two zones: the peripheral zone and the central gland. METHODS The proposed method is based on a modified version of the evidential C-means clustering algorithm. The evidential C-means optimization process was modified(More)
Within the framework of evidence theory, data fusion consists in obtaining a single belief function by the combination of several belief functions resulting from distinct information sources. The most popular rule of combination, called Dempster’s rule of combination (or the orthogonal sum), has several interesting mathematical properties such as(More)
The 3D-shape matching problem plays a crucial role in many applications, such as indexing or modeling, by example. Here, we present a novel approach to matching 3D objects in the presence of nonrigid transformation and partially similar models. In this paper, we use the representation of surfaces by 3D curves extracted around feature points. Indeed,(More)
In this paper we propose and study an evidential segmentation scheme of multi-echo MR images for the detection of brain tumors. We show that the modeling by means of evidence theory is well suited to the processing of redundant and complementary data as the MR images. Moreover neighborhood relationship between voxels is taken into account via Dempster’s(More)
PSI, EA 2120, Université & INSA de Rouen Place Emile Blondel, F-76131 Mont Saint Aignan Cedex Eric.Lefevre@insa-rouen.fr IRCOM-SIC, UMR CNRS 6615, Bat. SP2MI BP 30179, Bd Marie et Pierre Curie, F-86962 Chasseneuil du Poitou Cedex colot@sic.sp2mi.univ-poitiers.fr HEUDIASYC, UMR 6599 CNRS, Université de Technologie de Compiègne BP 20529, F-60205 Compiègne(More)
In this paper we introduce an evidential multi-source segmentation scheme for the extraction of prostate zonal anatomy using multi-parametric MRI. The Evidential C-Means (ECM) classifier was adapted to a segmentation scheme by introducing spatial neighbourhood-based relaxation step in its optimisation process. In order to do so, basic belief assignments on(More)