Diffusion-Based Semantic Segmentation of Lumbar Spine MRI Scans of Lower Back Pain Patients
This work addresses precise spine MRI analysis to potentially improve diagnosis and management of lower back pain, representing an incremental advancement in medical imaging.
The study tackled semantic segmentation of vertebrae, intervertebral discs, and spinal canal in lumbar spine MRI scans for lower back pain patients, achieving results that outperformed non-diffusion state-of-the-art models in identifying degenerated IVDs.
This study introduces a diffusion-based framework for robust and accurate segmenton of vertebrae, intervertebral discs (IVDs), and spinal canal from Magnetic Resonance Imaging~(MRI) scans of patients with low back pain (LBP), regardless of whether the scans are T1w or T2-weighted. The results showed that SpineSegDiff achieved comparable outperformed non-diffusion state-of-the-art models in the identification of degenerated IVDs. Our findings highlight the potential of diffusion models to improve LBP diagnosis and management through precise spine MRI analysis.