Mobile volume rendering and disease detection using deep learning algorithms

This paper introduces a system designed to convert 2D slices from Magnetic resonance imaging(MRI) and Computed Tomography(CT) scans into 3D images, facilitating mobile device-based diagnosis by medical professionals. Utilizing machine learning techniques tailored to specific image categories, the system processes Digital Imaging and Communications in Medicine(DICOM) images for disease detection. AWS cloud infrastructure, including S3 bucket, Relational Database Service(RDS), and DynamoDB, manages DICOM storage. The system delivers a final processed image displaying predicted diseases directly to the mobile screen. This innovative approach enhances medical imaging accessibility and diagnostic accuracy, offering a streamlined solution for healthcare professionals.