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Published in:
2014 | OriginalPaper | Chapter
Application-Driven MRI: Joint Reconstruction and Segmentation from Undersampled MRI Data
Authors : Jose Caballero, Wenjia Bai, Anthony N. Price, Daniel Rueckert, Joseph V. Hajnal
Published in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014
Publisher: Springer International Publishing
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Medical image segmentation has traditionally been regarded as a separate process from image acquisition and reconstruction, even though its performance directly depends on the quality and characteristics of these first stages of the imaging pipeline. Adopting an integrated acquisition-reconstruction-segmentation process can provide a more efficient and accurate solution. In this paper we propose a joint segmentation and reconstruction algorithm for undersampled magnetic resonance data. Merging a reconstructive patch-based sparse modelling and a discriminative Gaussian mixture modelling can produce images with enhanced edge information ultimately improving their segmentation.