Automatic Spine Curvature Estimation by a Top-Down Approach

被引：1

作者：

Zhao, Shixuan ^{[1
]}

Wang, Bo ^{[1
]}

Yang, Kaifu ^{[1
]}

Li, Yongjie ^{[1
]}

机构：

[1] Univ Elect Sci & Technol China, Sch Life Sci & Technol, MOE Key Lab Neuroinformat, Chengdu 610054, Peoples R China

来源：

COMPUTATIONAL METHODS AND CLINICAL APPLICATIONS FOR SPINE IMAGING, CSI 2019 | 2020年 / 11963卷

关键词：

AIS; Deep learning; Cobb angles; Spinal curvature;

D O I：

10.1007/978-3-030-39752-4_8

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Adolescent idiopathic scoliosis (AIS) is the most common type of spinal deformity in children in early puberty. Cobb angle is widely used in the diagnosis and treatment of scoliosis. However, existing Cobb angle measurement methods in clinical practice are time-consuming and unreliable. Accurate quantitative assessment of spinal curvature is an essential task in the clinical assessment and treatment planning of AIS. In this study, we proposed a top-down approach to accomplish the task of automatic spinal curvature estimation. We achieved 26.0535% of symmetric mean absolute percentage error (SMAPE).

引用

页码：75 / 80

页数：6

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