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- Title
A hybrid tissue segmentation approach for brain MR images.
- Authors
Song, Tao; Gasparovic, Charles; Andreasen, Nancy; Bockholt, Jeremy; Jamshidi, Mo; Lee, Roland R; Huang, Mingxiong
- Abstract
A novel hybrid algorithm for the tissue segmentation of brain magnetic resonance images is proposed. The core of the algorithm is a probabilistic neural network (PNN) in which weighting factors are added to the summation layer, such that partial volume effects can be taken into account in the modeling process. The mean vectors for the probability density function estimation and the corresponding weighting factors are generated by a hierarchical scheme involving a self-organizing map neural network and an expectation maximization algorithm. Unlike conventional PNN, this approach circumvents the need for training sets. Tissue segmentation results from various algorithms are compared and the effectiveness and robustness of the proposed approach are demonstrated.
- Subjects
BRAIN anatomy; ALGORITHMS; BIOLOGICAL models; COMPARATIVE studies; COMPUTER simulation; DIAGNOSTIC imaging; MAGNETIC resonance imaging; RESEARCH methodology; MEDICAL cooperation; ARTIFICIAL neural networks; PROBABILITY theory; RESEARCH; EVALUATION research
- Publication
Medical & Biological Engineering & Computing, 2006, Vol 44, Issue 1/2, p242
- ISSN
0140-0118
- Publication type
journal article
- DOI
10.1007/s11517-005-0021-1