Enhanced Detection of Multiple Sclerosis Using Recurrent Slice-wise Attention Network (RSANet) on Brain MRI Scans

Multiple Sclerosis (MS) is a degenerative disease of the central nervous system that is most commonly referred to as MS. For MS to be effectively treated, early and precise detection is essential. Earlier detection of Multiple Sclerosis (MS) based on Recurrent Slice-wise Attention Network (RSANet) under Brain MRI scanning has been studied. The analysis involved the use of an RSANet that trained and evaluated with the use of an MS- Sagittal; MS-Axial; Control-Sagittal; ControlAxial image dataset. RSANet employs a slice-wise attention mechanism to focus on important regions of MRI scans in this way boosting the ability of the model in discriminating between MS and control cases. Experimental results indicate that an RSANet yields higher accuracy, sensitivity, and specificity compared to the traditional CNNs and 3D CNNs. This shows that RSANet is able and thus qualified to emerge as a prominent clinical MS diagnostic tool.