Deep learning-based computer-aided diagnostic system for lumbar degenerative diseases classification using MRI

Motivation: Assisting radiologists in the diagnosis of degenerative diseases of the lumbar spine and reducing the workload of physicians. Goal(s): Building a deep learning-based CAD system for lumbar degenerative diseases to address the limitations of existing models and provide a more powerful and clinically relevant tool. Approach: Retrospective analysis of lumbar magnetic resonance imaging data and development of a lumbar CAD system for lumbar disc localization, binary classification, and multi-label diagnosis of degenerative diseases. Results: This lumbar CAD system achieves high disc localization success and classification accuracy in seven lumbar spine lesions. Impact: Our study demonstrates the feasibility of using deep learning to classify multiple lumbar spine diseases with strong performance, highlighting the potential of our CAD system to reduce physician workload in clinical applications.