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Technical Program
Paper Detail
| Paper: | MA-L3.2 |
| Session: | Biomedical Image Segmentation |
| Time: | Monday, October 9, 10:00 - 10:20 |
| Presentation: |
Lecture
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| Title: |
SEGMENTATION AND FUZZY-LOGIC CLASSIFICATION OF M-FISH CHROMOSOME IMAGES |
| Authors: |
Hyohoon Choi; University of Texas at Austin | | | | | Kenneth Castleman; Advanced Digital Imaging Research, LLC | | | | | Alan Bovik; University of Texas at Austin | | |
| Abstract: |
Multicolor fluorescence in-situ hybridization (M-FISH) technique provides color karyotyping that allows simultaneous analysis of numerical and structural abnormalities of whole human chromosomes. Currently available M-FISH systems exhibit misclassifications of multiple pixel regions that are often larger than the actual chromosomal rearrangement. This paper presents a novel unsupervised classification method based on fuzzy logic classification and a prior adjusted reclassification method. Utilizing the chromosome boundaries, the initial classification results improved signifi- cantly after the prior adjusted reclassification while keeping the translocations intact. This paper also presents a new segmentation method that combines both spectral and edge information. Ten M-FISH images from a publicly available database were used to test our methods. The segmentation accuracy was more than 98% on average. |
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