Automatic 3-D spine curve measurement in freehand ultrasound via structure-aware reinforcement learning spinous process localization.

Autor: Ran QY; The School of Biological Science and Medical Engineering, Southeast University, Nanjing, China; State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China; Jiangsu Key Laboratory of Biomaterials and Devices, Southeast University, Nanjing, China., Miao J; The School of Biological Science and Medical Engineering, Southeast University, Nanjing, China; Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, China., Zhou SP; The School of Biological Science and Medical Engineering, Southeast University, Nanjing, China; State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China; Jiangsu Key Laboratory of Biomaterials and Devices, Southeast University, Nanjing, China., Hua SH; The School of Biological Science and Medical Engineering, Southeast University, Nanjing, China; State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China; Jiangsu Key Laboratory of Biomaterials and Devices, Southeast University, Nanjing, China., He SY; The School of Biological Science and Medical Engineering, Southeast University, Nanjing, China; State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China; Jiangsu Key Laboratory of Biomaterials and Devices, Southeast University, Nanjing, China., Zhou P; The School of Biological Science and Medical Engineering, Southeast University, Nanjing, China., Wang HX; The Department of Rehabilitation Medicine, Zhongda Hospital, Southeast University, Nanjing, China., Zheng YP; The Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China., Zhou GQ; The School of Biological Science and Medical Engineering, Southeast University, Nanjing, China; State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China; Jiangsu Key Laboratory of Biomaterials and Devices, Southeast University, Nanjing, China. Electronic address: guangquan.zhou@seu.edu.cn.
Jazyk: angličtina
Zdroj: Ultrasonics [Ultrasonics] 2023 Jul; Vol. 132, pp. 107012. Date of Electronic Publication: 2023 Apr 11.
DOI: 10.1016/j.ultras.2023.107012
Abstrakt: Freehand 3-D ultrasound systems have been advanced in scoliosis assessment to avoid radiation hazards, especially for teenagers. This novel 3-D imaging method also makes it possible to evaluate the spine curvature automatically from the corresponding 3-D projection images. However, most approaches neglect the three-dimensional spine deformity by only using the rendering images, thus limiting their usage in clinical applications. In this study, we proposed a structure-aware localization model to directly identify the spinous processes for automatic 3-D spine curve measurement using the images acquired with freehand 3-D ultrasound imaging. The pivot is to leverage a novel reinforcement learning (RL) framework to localize the landmarks, which adopts a multi-scale agent to boost structure representation with positional information. We also introduced a structure similarity prediction mechanism to perceive the targets with apparent spinous process structures. Finally, a two-fold filtering strategy was proposed to screen the detected spinous processes landmarks iteratively, followed by a three-dimensional spine curve fitting for the spine curvature assessments. We evaluated the proposed model on 3-D ultrasound images among subjects with different scoliotic angles. The results showed that the mean localization accuracy of the proposed landmark localization algorithm was 5.95 pixels. Also, the curvature angles on the coronal plane obtained by the new method had a high linear correlation with those by manual measurement (R = 0.86, p < 0.001). These results demonstrated the potential of our proposed method for facilitating the 3-D assessment of scoliosis, especially for 3-D spine deformity assessment.
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2023 Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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