Robust semi-automatic segmentation method: an expert assistant tool for muscles in CT and MR data

• Published in: Computer methods in biomechanics and biomedical engineering. 2024-01, Vol.11 (7)
• Main Authors: Azimbagirad, Mehran, Dardenne, Guillaume, Ben Salem, Douraied, Werthel, Jean-David, Boux de Casson, François, Stindel, Eric, Garraud, Charles, Rémy-Néris, Olivier, Burdin, Valérie
• Format: Article
• Language: English
• Subjects: 3D spline interpolation; directed graph-structure; shoulder muscle; Thigh muscle
• ISSN: 2168-1163; 2168-1171
• DOI: 10.1080/21681163.2023.2301403

Image muscle segmentation is useful to quantitatively assess musculoskeletal diseases by extracting biomarkers such as shape, texture and water diffusivity metrics. Although volumetric manual segmentation is time consuming and a bottleneck in practice, fully automatic approaches are still in progress to reach an acceptable accuracy. In this paper, we provide a robust semi-automated tool to segment two musculoskeletal systems, i.e. thigh and shoulder in MRI and CT modalities, respectively. The tool only needs a few manually labelled cross-sections to build a directed graph-structure of corresponding points between the successive spaced slices. The boundaries of each muscle are obtained by performing a spline interpolation based on the directed graph-structure. Each muscle label and its corresponding 3D mesh are deduced using post-processing techniques. We evaluated the tool on 26 MRI thighs and 16 CT shoulders. Three metrics along with inter-muscle overlapping were employed to evaluate the tool by comparison to an expert manual segmentation and a publicly available tools (ITK-SNAP, 3D Slicer). The results showed a mean Dice $0.988 \pm 0.003$ 0.988 ± 0.003 , and Hausdorff Distance $4.86 \pm 1.67$ 4.86 ± 1.67 mm in comparison to the manual reference for thigh muscle segmentation, and a mean Dice $0.961 \pm 0.005$ 0.961 ± 0.005 and Hausdorff Distance $2.42 \pm 0.79$ 2.42 ± 0.79 mm for shoulder muscle segmentation, outperformed the other methods. The tool is proposed as slicer module available at https://github.com/latimagine/SlicerSpline .