marker-controlled watershed algorithm

This paper proposes a novel method for rapidly and accurately detecting multiple sclerosis (MS) lesions and analyzing the progression of lesions and the disease based on differences between histograms of hemispheres and volumetric changes in brain regions over time. The brightness and contrast of pixels are first improved, and MRI slices are then analyzed to detect and eliminate the effects of motion artifacts while imaging. However, an accurate diagnosis tracks changes in volumes of brain regions caused by plaques emerging on brain MRIs in white matter, gray matter, and cerebrospinal fluid (CSF) and the concurrent analysis of differences between histograms of hemispheres. The marker-controlled watershed algorithm was employed to extract MS lesions and plaques. Various MRI centers differ in imaging diameters for which there are no unified standards, leading to different MRI slices. Hence, an individual's two MRI slices of two different occasions are not comparable. Measuring the brain volume can make the proposed method independent of the imaging diameter. This study analyzed the patients with at least three imaging records in the archives of imaging centers. The images were collected from Pars MRI Center and Hajar Hospital MRI Center in Shahrekord, Chararmahal and Bakhtiari Province, Iran. Both centers used Avanto MRI devices and performed imaging at 1 T and 1.5 T, respectively.