Automatic multiple sclerosis lesion detection in brain MRI by FLAIR thresholding

作者：Cabezas Mariano; Oliver Arnau; Roura Eloy; Freixenet Jordi; Vilanova Joan C; Ramio Torrenta Lluis; Rovira Alex; Llado Xavier^*

来源：Computer Methods and Programs in Biomedicine, 2014, 115(3): 147-161.

DOI：10.1016/j.cmpb.2014.04.006

• Multiple sclerosis
• Lesion segmentation
• MRI

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.

• 出版日期2014-7