Preliminary Study on Appearance-Based Detection of Anatomical Point Landmarks in Body Trunk CT Images

被引：0

作者：

Nemoto, Mitsutaka ^{[1
]}

Nomura, Yukihiro ^{[1
]}

Hanaoka, Shohei ^{[1
]}

Masutani, Yoshitaka ^{[1
]}

Yoshikawa, Takeharu ^{[1
]}

Hayashi, Naoto ^{[1
]}

Yoshioka, Naoki ^{[1
]}

Ohtomo, Kuni ^{[1
]}

机构：

[1] Tokyo Univ Hosp, Dept Radiol, Bunkyo Ku, Tokyo 1138655, Japan

来源：

MACHINE LEARNING IN MEDICAL IMAGING | 2010年 / 6357卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Anatomical point landmarks as most primitive anatomical knowledge are useful for medical image understanding. In this study, we propose a detection method for anatomical point landmark based on appearance models, which include gray-level statistical variations at point landmarks and their surrounding area. The models are built based on results of Principal Component Analysis (PCA) of sample data sets. In addition, we employed generative learning method by transforming ROT of sample data. In this study, we evaluated our method with 24 data sets of body trunk CT images and obtained 95.8 +/- 7.3 % of the average sensitivity in 28 landmarks.

引用

页码：174 / 181

页数：8

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