Areej A. Malibari1, Reem Alshahrani2, Fahd N. Al-Wesabi3,*, Siwar Ben Haj Hassine3, Mimouna Abdullah Alkhonaini4, Anwer Mustafa Hilal5
CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3799-3813, 2022, DOI:10.32604/cmc.2022.026131
Abstract Medical image processing becomes a hot research topic in healthcare sector for effective decision making and diagnoses of diseases. Magnetic resonance imaging (MRI) is a widely utilized tool for the classification and detection of prostate cancer. Since the manual screening process of prostate cancer is difficult, automated diagnostic methods become essential. This study develops a novel Deep Learning based Prostate Cancer Classification (DTL-PSCC) model using MRI images. The presented DTL-PSCC technique encompasses EfficientNet based feature extractor for the generation of a set of feature vectors. In addition, the fuzzy k-nearest neighbour (FKNN) model is utilized for classification process where the… More >
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