Comput Methods Programs Biomed - Automatic multiple sclerosis lesion detection in brain MRI by FLAIR thresholding.

Tópicos

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Resumo

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.

Resumo Limpo

magnet reson imag mri frequent use detect segment multipl sclerosi lesion due detail rich inform provid present modifi expectationmaximis algorithm segment brain tissu white matter grey matter cerebrospin fluid well partial volum class contain fluid grey matter algorithm provid initi segment lesion separ tissu thus second step need find second step involv threshold flair imag follow regionwis refin discard fals detect evalu propos use databas case compris t imag data three differ hospit differ scanner machin variabl lesion load per case result databas point higher accuraci compar two best stateoftheart approach

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