A machine learning approach for body part recognition based on CT images

Keigo Nakamura; Yuanzhong Li; Wataru Ito; Kazuo Shimura

doi:10.1117/12.768480

11 March 2008 A machine learning approach for body part recognition based on CT images

Keigo Nakamura, Yuanzhong Li, Wataru Ito, Kazuo Shimura

Author Affiliations +

Proceedings Volume 6914, Medical Imaging 2008: Image Processing; 69141U (2008) https://doi.org/10.1117/12.768480
Event: Medical Imaging, 2008, San Diego, California, United States

Abstract

Body part recognition based on CT slice images is very important for many applications in PACS and CAD systems. In this paper, we propose a novel approach that can recognize which body part a slice image belongs to robustly. We focus on how to effectively express and use the unique statistical information of the correlation between the CT value and the position information of each body part. We apply the machine learning method AdaBoost to express and use this statistical information. Our approach consists of a training process and a recognition process. In the training process, we first define the whole body using a set of specific classes to ensure that training images in the same class have a high similarity, and prepare a training image set (positive samples and negative samples) for each class. Second, the training images are normalized to a fixed size and rotation in each class. Third, features are calculated for each normalized training image. Finally, AdaBoosted histogram classifiers are trained. After the training process, each class has its own classifiers. In the recognition process, given a series of CT images, the scores of all classes for each slice image are calculated based on the classifiers obtained in the training process. Then, based on the scores of each slice and a simple model of body part sequence continuity, we use dynamic programming (DP) to eliminate false recognition results. Experimental results on 440 unknown series including lesions show that our approach has high a recognition rate.

Citation Download Citation

Keigo Nakamura, Yuanzhong Li, Wataru Ito, and Kazuo Shimura "A machine learning approach for body part recognition based on CT images", Proc. SPIE 6914, Medical Imaging 2008: Image Processing, 69141U (11 March 2008); https://doi.org/10.1117/12.768480

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