Segmentation of the Striatum from MR Brain Images to Calculate the -TRODAT-1 Binding Ratio in SPECT Images
Author(s) -
ChingFen Jiang,
ChiungChih Chang,
ShuHua Huang,
ChungHsien Wu
Publication year - 2013
Publication title -
computational and mathematical methods in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.462
H-Index - 48
eISSN - 1748-6718
pISSN - 1748-670X
DOI - 10.1155/2013/593175
Subject(s) - striatum , segmentation , nuclear medicine , reproducibility , spect imaging , artificial intelligence , computer science , pattern recognition (psychology) , computer vision , medicine , psychology , neuroscience , mathematics , statistics , dopamine
Quantification of regional 99m Tc-TRODAT-1 binding ratio in the striatum regions in SPECT images is essential for differential diagnosis between Alzheimer's and Parkinson's diseases. Defining the region of the striatum in the SPECT image is the first step toward success in the quantification of the TRODAT-1 binding ratio. However, because SPECT images reveal insufficient information regarding the anatomical structure of the brain, correct delineation of the striatum directly from the SPECT image is almost impossible. We present a method integrating the active contour model and the hybrid registration technique to extract regions from MR T1-weighted images and map them into the corresponding SPECT images. Results from three normal subjects suggest that the segmentation accuracy using the proposed method was compatible with the expert decision but has a higher efficiency and reproducibility than manual delineation. The binding ratio derived by this method correlated well ( R 2 = 0.76) with those values calculated by commercial software, suggesting the feasibility of the proposed method.
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