Camille Izard

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In medical imaging, finding landmarks that provide biologically meaningful correspondences is often a challenging and time-consuming manual task. In this paper we propose a generic and simple algorithm for landmarking non-cortical brain structures automatically. We use a probabilistic model of the image intensities based on the deformation of a tissue(More)
This paper will be published in Medical Imaging 2005 Proceedings and is made available as an electronic preprint with permission of SPIE. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplicattion of any material in this paper for a fee(More)
We present a generic statistical deformable model for gray level medical images and propose to use it for template matching. Template matching methods usually rely on the arbitrary choice of a cost function and a template. Statistical models , on the other hand, allow us to derive optimal learning and matching algorithms from the modeling assumptions using(More)
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