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

• Published in: NeuroImage (Orlando, Fla.) Vol. 76; pp. 11 - 23
• Main Authors: Tong, Tong, Wolz, Robin, Coupé, Pierrick, Hajnal, Joseph V., Rueckert, Daniel
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Inc 01.08.2013; Elsevier; Elsevier Limited
• Subjects: Adult; Aged; Automation; Bioengineering; Biological and medical sciences; Brain Mapping - methods; Computer Science; Dictionaries; Discrimination Learning - physiology; Discriminative dictionary learning; Distance learning; Engineering Sciences; Female; Fundamental and applied biological sciences. Psychology; Hippocampus - physiology; Humans; Image Interpretation, Computer-Assisted - methods; Image Processing; Labeling; Libraries; Life Sciences; Magnetic Resonance Imaging - methods; Male; Medical Imaging; Methods; NMR; Nuclear magnetic resonance; Patch-based segmentation; Registration; Signal and Image processing; Sparse representation; Structural MR images; Vertebrates: nervous system and sense organs; Structural MR images; Patch-based segmentation; Sparse representation; Discriminative dictionary learning; Learning; Acquisition process; Segmentation; Central nervous system; Hippocampus; Encephalon

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 reconstru...