Automatic Contouring of Spinal Vertebrae on X-Ray using a Novel Sandwich U-Net Architecture

• URL: http://arxiv.org/abs/2507.09158v1
• Date: Sat, 12 Jul 2025 06:40:18 GMT
• Title: Automatic Contouring of Spinal Vertebrae on X-Ray using a Novel Sandwich U-Net Architecture
• Authors: Sunil Munthumoduku Krishna Murthy, Kumar Rajamani, Srividya Tirunellai Rajamani, Yupei Li, Qiyang Sun, Bjoern W. Schuller,
• Abstract summary: We propose a novel U-Net variation designed to accurately segment thoracic vertebrae from anteroposterior view on X-Ray images.<n>Our proposed approach, incorporating a sandwich" U-Net structure with dual activation functions, achieves a 4.1% improvement in Dice score compared to the baseline U-Net model.
• Score: 2.170477444239546
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In spinal vertebral mobility disease, accurately extracting and contouring vertebrae is essential for assessing mobility impairments and monitoring variations during flexion-extension movements. Precise vertebral contouring plays a crucial role in surgical planning; however, this process is traditionally performed manually by radiologists or surgeons, making it labour-intensive, time-consuming, and prone to human error. In particular, mobility disease analysis requires the individual contouring of each vertebra, which is both tedious and susceptible to inconsistencies. Automated methods provide a more efficient alternative, enabling vertebra identification, segmentation, and contouring with greater accuracy and reduced time consumption. In this study, we propose a novel U-Net variation designed to accurately segment thoracic vertebrae from anteroposterior view on X-Ray images. Our proposed approach, incorporating a ``sandwich" U-Net structure with dual activation functions, achieves a 4.1\% improvement in Dice score compared to the baseline U-Net model, enhancing segmentation accuracy while ensuring reliable vertebral contour extraction.

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