A unified framework for concurrent detection of anatomical landmarks for medical image understanding

Mitsutaka Nemoto; Yoshitaka Masutani; Shouhei Hanaoka; Yukihiro Nomura; Takeharu Yoshikawa; Naoto Hayashi; Naoki Yoshioka; Kuni Ohtomo

doi:10.1117/12.878327

14 March 2011 A unified framework for concurrent detection of anatomical landmarks for medical image understanding

Mitsutaka Nemoto, Yoshitaka Masutani, Shouhei Hanaoka, Yukihiro Nomura, Takeharu Yoshikawa, Naoto Hayashi, Naoki Yoshioka, Kuni Ohtomo

Author Affiliations +

Proceedings Volume 7962, Medical Imaging 2011: Image Processing; 79623E (2011) https://doi.org/10.1117/12.878327
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States

Abstract

Anatomical landmarks are useful as the primitive anatomical knowledge for medical image understanding. In this study, we construct a unified framework for automated detection of anatomical landmarks distributed within the human body. Our framework includes the following three elements; (1) initial candidate detection based on a local appearance matching technique based on appearance models built by PCA and the generative learning, (2) false positive elimination using classifier ensembles trained by MadaBoost, and (3) final landmark set determination based on a combination optimization method by Gibbs sampling with a priori knowledge of inter-landmark distances. In evaluation of our methods with 50 data sets of body trunk CT, the average sensitivity in detecting candidates of 165 landmarks was 0.948 ± 0.084 while 55 landmarks were detected with 100 % sensitivity. Initially, the amount of false positives per landmark was 462.2 ± 865.1 per case on average, then they were reduced to 152.8 ± 363.9 per case by the MadaBoost classifier ensembles without miss-elimination of the true landmarks. Finally 89.1 % of landmarks were correctly selected by the final combination optimization. These results showed that our framework is promising for an initial step for the subsequent anatomical structure recognition.

Citation Download Citation

Mitsutaka Nemoto, Yoshitaka Masutani, Shouhei Hanaoka, Yukihiro Nomura, Takeharu Yoshikawa, Naoto Hayashi, Naoki Yoshioka, and Kuni Ohtomo "A unified framework for concurrent detection of anatomical landmarks for medical image understanding", Proc. SPIE 7962, Medical Imaging 2011: Image Processing, 79623E (14 March 2011); https://doi.org/10.1117/12.878327

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available