Title :
Unsupervised medical image analysis by multiscale FNM modeling and MRF relaxation labeling
Author :
Wang, Yue ; Adali, Tülay ; Lei, Tianhu
Author_Institution :
Dept. of Electr. Eng., Maryland Univ., Baltimore, MD, USA
Abstract :
We derive two types of block-wise FNM model for pixel images by incorporating local context. The self-learning is then formulated as an information match problem and solved by first estimating model parameters to initialize ML solution and then conducting finer segmentation through MRF relaxation
Keywords :
Markov processes; image matching; image segmentation; maximum likelihood estimation; medical image processing; random processes; unsupervised learning; ML solution; MRF relaxation labeling; Markov random fields; block-wise FNM model; image segmentation; information match problem; local context; multiscale FNM modeling; parameter estimation; pixel images; self-learning; unsupervised medical image analysis; Bayesian methods; Biomedical imaging; Context modeling; Image analysis; Image segmentation; Labeling; Maximum likelihood estimation; Parameter estimation; Pixel; Stochastic processes;
Conference_Titel :
Information Theory and Statistics, 1994. Proceedings., 1994 IEEE-IMS Workshop on
Conference_Location :
Alexandria, VA
Print_ISBN :
0-7803-2761-6
DOI :
10.1109/WITS.1994.513928
