# Diffusion-Based Semantic Segmentation of Lumbar Spine MRI Scans of Lower Back Pain Patients

Source: [Diffusion-Based Semantic Segmentation of Lumbar Spine MRI Scans of Lower Back Pain Patients](<https://www.sota2.com/research/paper/68fa75bd1e209131cea699f9>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T03:40:43.406Z

Authors: Maria Monzon, Thomas Iff, Ender Konukoglu, Catherine R. Jutzeler

Published: 2024-11-16T09:22:46.000Z

## Abstract

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.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2411.10755>)

[PDF](<https://arxiv.org/pdf/2411.10755.pdf>)