An information bottleneck-based optimal transport network for automated diagnosis of spinal diseases.
Experimental results on real spinal X-ray dataset demonstrate that the proposed model outperforms existing methods in classification accuracy, generalization capability, and feature discriminability, validating its effectiveness and application potential in intelligent spinal image diagnosis.