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Recent improvements of fetal MRI acquisitions now allow three-dimensional segmentation of fetal structures, to extract bio-metrical measures for pregnancy follow-up. Automation of the segmentation process remains a difficult challenge, given the complexity of the fetal organs and their spatial organization. As a starting point, we propose in this paper a fully automated segmentation method to localize...
A statistical variational framework is proposed for the fetus and uterus segmentation in ultrasound images. The Rayleigh and exponential distributions are used to model the pixel intensity. An energy is derived to perform an optimal partition of the 3D data into two classes corresponding to these two distributions, in a Bayesian MAP framework. Some numerical difficulties are raised by the combination...
An automated, level-set based, segmentation framework is proposed in this work for computation of tumoral volumes on mice brain bearing gliomal tumors. Tl and T2 weighted MRI images were acquired to monitor tumor growth, at different time points. We developed an original multi-phase and multi-channel segmentation method, based on the level set framework of Chan and Vese, to facilitate the estimation...
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