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Automatic delineation of Gd enhancements on magnetic resonance images in multiple sclerosis
Author(s) -
He Renjie,
Narayana Ponnada A.
Publication year - 2002
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.1487422
Subject(s) - choroid plexus , magnetic resonance imaging , segmentation , multiple sclerosis , artificial intelligence , contrast (vision) , computer science , image segmentation , pattern recognition (psychology) , computer vision , medicine , radiology , central nervous system , psychiatry , endocrinology
A method for automatic identification and delineation of contrast‐enhanced multiple sclerosis (MS) lesions on brain magnetic resonance images is described. This method relies on adaptive local segmentation derived from the morphological “open” and “reconstruction” operations on gray scale images for identification of both lesion and nonlesion enhancements. Nonlesion enhancements from vasculature and extrameningeal tissues are identified by exploiting their topologic relationship to the brain mask. Enhancing structures without a blood–brain‐barrier, such as choroid plexus, are identified and eliminated by spatially mapping the locations of the MS lesions visualized on dual echo images onto the post‐contrast images. Delineation of enhancements is realized using fuzzy connectivity. Both the detection and delineation results are validated using statistical methods.

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