Segmentation of the Scaphoid Bone in Ultrasound Images

Current Directions in Biomedical Engineering

Welle Kristian¹  Hohlmann Benjamin²  Radermacher Klaus³  Brößner Peter³ 

[1] Orthopaedics and Traumatology, University ClinicBonn, Germany;RWTH Aachen, Pauwelsstraße 20,Aachen, Germany;RWTH Aachen,Aachen, Germany;

关键词: ultrasound imaging;    machine learning;    segmentation;    scaphoid fixation;   

DOI  :  10.1515/cdbme-2021-1017

来源: DOAJ

【 摘 要 】

For the percutaneous fixation of scaphoid fractures, navigated approaches have been proposed to facilitate screw placement. Based on ultrasound imaging, navigation can be carried out in a cost-effective and fast manner, furthermore avoiding harmful radiation. For this purpose, a fast and efficient architecture for the automated segmentation of scaphoid bone in ultrasound volume images is needed. Methods: For 2D segmentation of the scaphoid, two architectures are taken into account: 2D nnUNet and Deeplabv3+. These architectures are trained and evaluated on a newly created dataset consisting of 67 annotated in-vivo ultrasound volume images (4576 slice images). Results: In terms of Dice coefficient, the 2D nnUNet achieves 0.67 compared to 0.57 for the Deeplabv3+. In terms of distance metrics, the 2D nnUNet shows an average symmetric surface distance error of 0.66mm, while the Deeplabv3+ achieves 0.55mm. Conclusion: Fast and accurate segmentation of the scaphoid in ultrasound volumes is feasible. Both architectures show competitive results.

【 授权许可】

Unknown