Thoratic Spine Segmentation Based on CT Images

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Abstract
Automatic vertebrae localization and segmentation in computed tomography (CT) are fundamental for computer-aided detection (CADe) and computer-aided diagnosis (CADx) systems. However, they remain challenging due to the high variation in spinal anatomy among patients. In this paper, we propose a simple, model-free approach for automatic CT vertebrae localization and segmentation. The segmentation pipeline consists of 3 stages. In the first stage the center line of the spinal cord is estimated using convolution. In the second stage a baseline segmentation of the spine is created using morphological reconstruction and other classical image processing algorithms. Finally, the baseline spine segmentation is refined by limiting its boundaries using simple heuristics based on expert knowledge. We evaluated our method on the COVID-19 subdataset of the CTSpine1K dataset. Our solution achieved a dice coefficient of 0.8160±0.0432 (mean±std) and an intersection over union of 0.6914±0.0618 for spine segmentation. The experimental results have demonstrated the feasibility of the proposed method in a real environment.- Title
- Thoratic Spine Segmentation Based on CT Images
- Author
- Révy, Gábor
- Hadházi, Dániel
- Hullám, Gábor
- Date of issue
- 2023
- Access level
- Open access
- Copyright owner
- Szerző
- Conference title
- 30th Minisymposium of the Department of Measurement and Information Systems
- Conference place
- Budapest
- Conference date
- 2023.02.06-2023.02.07.
- Language
- en
- Page
- 25 - 28
- Subject
- spine segmentation, CT, image processing, expert system
- Version
- Post print
- Identifiers
- DOI: 10.3311/minisy2023-007
- Title of the container document
- Proceedings of the 30th Minisymposium
- ISBN, e-ISBN
- 978-963-421-904-0
- Document type
- könyvfejezet
- Document genre
- Konferenciacikk
- University
- Budapest University of Technology and Economics
- Faculty
- Faculty of Electrical Engineering and Informatics
- Department
- Department of Measurement and Information Systems