The research on tissue segmentation for brain multi-spectral MR image
Author(s): ZHOU Xiaodong, BAO Shanglian, LI Dejun
Pages: 89-91,121
Year: 2003 Issue: 2
Journal: CHINESE JOURNAL OF MEDICAL PHYSICS
Keyword: multi-spectral MRI; segmentation; kNN; FNP; neighborhood rule;
Abstract: Segmentation for brain tissue becomes more and more important in clinical diagnosis and treatment for dis-eases as well as for basic research such as for virtual human subjects. In this paper, pattern recognition methods wereused to perform the segmentation for Multi-Spectral MR images. The k Nearest Neighbor (kNN) and the Fuzzy NearestPrototype (FNP) algorithms[1]were adopted. Combination of the consideration on the feature of MR image and the anatomicknowledge, a set of neighborhood rules were established. Generally, kNN and FNP algorithms classify the samples intheir state space, ignoring the information between pixels in the image. The neighborhood rules were added to deter-mine the uncertain results after state space classification. The result from the segmentation was obviously better thenthat from previous kNN or FNP algorithm.
Pages: 89-91,121
Year: 2003 Issue: 2
Journal: CHINESE JOURNAL OF MEDICAL PHYSICS
Keyword: multi-spectral MRI; segmentation; kNN; FNP; neighborhood rule;
Abstract: Segmentation for brain tissue becomes more and more important in clinical diagnosis and treatment for dis-eases as well as for basic research such as for virtual human subjects. In this paper, pattern recognition methods wereused to perform the segmentation for Multi-Spectral MR images. The k Nearest Neighbor (kNN) and the Fuzzy NearestPrototype (FNP) algorithms[1]were adopted. Combination of the consideration on the feature of MR image and the anatomicknowledge, a set of neighborhood rules were established. Generally, kNN and FNP algorithms classify the samples intheir state space, ignoring the information between pixels in the image. The neighborhood rules were added to deter-mine the uncertain results after state space classification. The result from the segmentation was obviously better thenthat from previous kNN or FNP algorithm.
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