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Updated: Feb 15, 2026
Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
Published on: November 30, 2022
Computed Tomography Images of the Scapula Taken With Reduced Dose Can Yield Segmented Models of Sufficient Accuracy:
Michiel Herteleer, Sanne Vancleef1, Stefaan Nijs
1Department of Mechanical Engineering, Division Biomechanical Engineering, Heverlee.
Objective:
The aim of the study was to investigate the influence of tube current reduction on the segmentation accuracy of the scapula.
Methods:
A human cadaver was computed tomography scanned multiple times while reducing tube current amperage. The images were segmented using 2 different segmentation methods (N = 28). Subsequently the scapula was dissected and all soft tissues were removed. An optical laser scan of the dissected scapula was aligned and compared with the segmented meshes of the different computed tomography scans.
Results:
The mesh accuracy remained fairly constant with diminishing tube currents. All segmented meshes had a larger volume than the reference mesh (n = 27). The mean 3-dimensional deviation varied between 1.17 mm (max) and -0.759 mm (min) and the total mean (SD) 3-dimensional deviation was -0.45 (0.38) mm. Radiation dosages were reduced from 7.1 to 0.3 mSv.
Conclusions:
Computed tomography tube current can be largely reduced without losing the surface segmentation accuracy of segmented scapula meshes.
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