H. M. Rehan Afzal1,2,*, Suhuai Luo1, Saadallah Ramadan1,2, Jeannette Lechner-Scott1,2,3, Mohammad Ruhul Amin3, Jiaming Li4, M. Kamran Afzal5
CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 977-991, 2021, DOI:10.32604/cmc.2020.012448
Abstract The diagnosis of multiple sclerosis (MS) is based on accurate detection
of lesions on magnetic resonance imaging (MRI) which also provides ongoing
essential information about the progression and status of the disease. Manual
detection of lesions is very time consuming and lacks accuracy. Most of the
lesions are difficult to detect manually, especially within the grey matter. This
paper proposes a novel and fully automated convolution neural network (CNN)
approach to segment lesions. The proposed system consists of two 2D patchwise
CNNs which can segment lesions more accurately and robustly. The first CNN
network is implemented to segment lesions accurately,… More >
Login
Register
