用扩散模型精准分割腰痛患者脊柱MRI，提升退变椎间盘识别
Diffusion-Based Semantic Segmentation of Lumbar Spine MRI Scans of Lower Back Pain Patients
- 基于扩散模型实现多模态MRI的脊柱结构分割
- 在退变椎间盘识别上超越非扩散类先进模型
- 适合医学影像分析与智能诊断研究者参考
本研究提出一种基于扩散模型的框架，用于对患有下腰痛（LBP）患者的磁共振成像（MRI）扫描进行鲁棒且准确的椎体、椎间盘（IVDs）和脊髓腔分割，适用于T1加权或T2加权图像。结果表明，SpineSegDiff在识别退变椎间盘方面表现优于现有非扩散类先进模型。研究凸显了扩散模型在通过精确脊柱MRI分析提升下腰痛诊断与管理方面的潜力。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。