Automatic multiple sclerosis lesion detection in brain MRI by FLAIR thresholding |
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Authors: | Mariano Cabezas,Arnau Oliver,Eloy Roura,Jordi Freixenet,Joan C. Vilanova,Lluí s Ramió -Torrentà ,À lex Rovira,Xavier Lladó |
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Affiliation: | 1. Department of Computer Architecture and Technology, University of Girona, Spain;2. Girona Magnetic Resonance Center, Spain;3. Multiple Sclerosis and Neuroimmunology Unit, Dr. Josep Trueta University Hospital, Spain;4. Magnetic Resonance Unit, Department of Radiology, Vall d’Hebron University Hospital, Spain |
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Abstract: | Magnetic resonance imaging (MRI) is frequently used to detect and segment multiple sclerosis lesions due to the detailed and rich information provided. We present a modified expectation-maximisation algorithm to segment brain tissues (white matter, grey matter, and cerebro-spinal fluid) as well as a partial volume class containing fluid and grey matter. This algorithm provides an initial segmentation in which lesions are not separated from tissue, thus a second step is needed to find them. This second step involves the thresholding of the FLAIR image, followed by a regionwise refinement to discard false detections. To evaluate the proposal, we used a database with 45 cases comprising 1.5T imaging data from three different hospitals with different scanner machines and with a variable lesion load per case. The results for our database point out to a higher accuracy when compared to two of the best state-of-the-art approaches. |
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Keywords: | Multiple sclerosis Lesion segmentation MRI |
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