Automatic Segmentation and Measurement on Knee Computerized Tomography Images for Patellar Dislocation Diagnosis

被引：8

作者：

Sun, Limin ^{[1
]}

Kong, Qi ^{[2
]}

Huang, Yan ^{[1
]}

Yang, Jiushan ^{[3
]}

Wang, Shaoshan ^{[3
]}

Zou, Ruiqi ^{[3
]}

Yin, Yilong ^{[1
]}

Peng, Jingliang ^{[1
]}

机构：

[1] Shandong Univ, Sch Software, Jinan 250101, Shandong, Peoples R China

[2] State Grid Anhui Elect Power Co, Hefei 230061, Anhui, Peoples R China

[3] Shandong Univ Tradit Chinese Med, Affiliated Hosp 1, Jinan 250014, Shandong, Peoples R China

来源：

COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE | 2020年 / 2020卷

基金：

中国国家自然科学基金;

关键词：

ACTIVE CONTOURS DRIVEN; BIAS FIELD ESTIMATION;

D O I：

10.1155/2020/1782531

中图分类号：

Q [生物科学];

学科分类号：

090105 [作物生产系统与生态工程];

摘要：

Traditionally, for diagnosing patellar dislocation, clinicians make manual geometric measurements on computerized tomography (CT) images taken in the knee area, which is often complex and error-prone. Therefore, we develop a prototype CAD system for automatic measurement and diagnosis. We firstly segment the patella and the femur regions on the CT images and then measure two geometric quantities, patellar tilt angle (PTA), and patellar lateral shift (PLS) automatically on the segmentation results, which are finally used to assist in diagnoses. The proposed quantities are proved valid and the proposed algorithms are proved effective by experiments.

引用

页数：13

共 36 条

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