Jean-Philippe Thirana

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This paper presents a computer-aided diagnosis system for pigmented skin lesions, with solutions for the lesion boundary detection and for the quantification of the degree of symmetry. Lesion detection results were validated by expert dermatologists, who also provided hand-drawn boundaries of the lesions. These reference boundaries were not used as a gold(More)
  • Dominique Zossoa, Benoı̂t Le Callennecb, Meritxell Bach Cuadraa, Kamiar Aminianb, Brigitte M. Jollesc, Jean-Philippe Thirana
  • 2008
In this paper we present a new method to track bone movements in stereoscopic X-ray image series of the knee joint. The method is based on two different X-ray image sets: a rotational series of acquisitions of the still subject knee that allows the tomographic reconstruction of the three-dimensional volume (model), and a stereoscopic image series of(More)
Detecting faces in images is a key step in numerous computer vision applications, such as face recognition or facial expression analysis. Automatic face detection is a difficult task because of the large face intra-class variability which is due to the important influence of the environmental conditions on the face appearance. We propose new features based(More)
  • Jason D. McEwena, Gilles Puya, Jean-Philippe Thirana, Pierre Vandergheynsta, Dimitri Van De Villeb, Yves Wiauxa
  • 2011
We discuss a novel sampling theorem on the sphere developed by McEwen & Wiaux recently through an association between the sphere and the torus. To represent a band-limited signal exactly, this new sampling theorem requires less than half the number of samples of other equiangular sampling theorems on the sphere, such as the canonical Driscoll & Healy(More)
Kernel matching pursuit is a greedy algorithm for building an approximation of a discriminant function as a linear combination of some basis functions selected from a kernel-induced dictionary. Here we propose a modification of the kernel matching pursuit algorithm that aims at making the method practical for large datasets. Starting from an approximating(More)
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