publication . Article . 2013

Segmentation of MR images via discriminative dictionary learning and sparse coding: Application to hippocampus labeling.

Tong, Tong; Wolz, Robin; Coupe, Pierrick; Hajnal, Joseph V.; Rueckert, Daniel;
Open Access
  • Published: 21 Mar 2013 Journal: NeuroImage, volume 76, pages 11-23 (issn: 1053-8119, Copyright policy)
  • Publisher: Elsevier BV
Abstract
International audience; We propose a novel method for the automatic segmentation of brain MRI images by using discriminative dictionary learning and sparse coding techniques. In the proposed method, dictionaries and classifiers are learned simultaneously from a set of brain atlases, which can then be used for the reconstruction and segmentation of an unseen target image. The proposed segmentation strategy is based on image reconstruction, which is in contrast to most existing atlas-based labeling approaches that rely on comparing image similarities between atlases and target images. In addition, we propose a Fixed Discriminative Dictionary Learning for Segmentat...
Subjects
ACM Computing Classification System: ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
free text keywords: Cognitive Neuroscience, Neurology, Image segmentation, Artificial intelligence, business.industry, business, Segmentation-based object categorization, Sparse approximation, Sørensen–Dice coefficient, Scale-space segmentation, Discriminative model, Iterative reconstruction, Pattern recognition, Computer vision, Segmentation, Computer science, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [SDV.IB]Life Sciences [q-bio]/Bioengineering
Funded by
NIH| Alzheimers Disease Neuroimaging Initiative
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 1U01AG024904-01
  • Funding stream: NATIONAL INSTITUTE ON AGING
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