Ping-Feng Chen

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We propose a constrained version of Mumford and Shah's (1989) segmentation model with an information-theoretic point of view in order to devise a systematic procedure to segment brain magnetic resonance imaging (MRI) data for parametric T(1)-Map and T(1)-weighted images, in both 2-D and 3D settings. Incorporation of a tuning weight in particular adds a(More)
In this paper we propose a constrained version of Mumford-Shah's[1] segmentation with an information-theoretic point of view[2] in order to devise a systematic procedure to segment brain MRI data for two modalities of parametric T 1-Map and T 1-weighted images in both 2-D and 3-D settings. The incorporation of a tuning weight in particular adds a(More)
In this paper we propose to jointly segment and register objects of interest in layered images. Layered imaging refers to imageries taken from different perspectives and possibly by different sensors. Registration and segmentation are therefore the two main tasks which contribute to the bottom level, data alignment, of the multisensor data fusion(More)
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