Paper:
Views over last 60 days: 546
A Classification Algorithm of Abdominal Ultrasound Images in Medical Practice for Secondary Uses
Yutaka Hatakeyama, Hiromi Kataoka, Noriaki Nakajima,
Teruaki Watabe, and Yoshiyasu Okuhara
Center of Medical Information Science, Kochi University, Kohasu, Oko-cho, Nankoku, Kochi 783-8506, Japan
Received:July 9, 2009Accepted:December 10, 2009Published:March 20, 2010
Keywords:ultrasonic test image, calcification, abdomen test
Abstract
A classification algorithm for abdominal organs in ultrasonic test images based on the operator’s knowledge is proposed. This is in order to use the medical images included in medical charts for secondary uses, e.g., medical data analysis. It makes a correlation between target organs in test images and search unit information on the body mark region. In the central region of abdominal images, target organs are uniquely determined through recognition of the liver region and in consideration of the location of the diaphragm. A classification experiment, done using 600,000 real test images taken at the Kochi Medical School Hospital from 2004 to 2008, was carried out to evaluate the performance of the proposed system in terms of accuracy rate of detection of the body mark region and diaphragm region. The proposed algorithm constitutes an essential classification system for the secondary use of a large database of ultrasound images taken in the course of medical practice.
Cite this article as:Y. Hatakeyama, H. Kataoka, N. Nakajima, T. Watabe, and Y. Okuhara, “A Classification Algorithm of Abdominal Ultrasound Images in Medical Practice for Secondary Uses,” J. Adv. Comput. Intell. Intell. Inform., Vol.14 No.2, pp. 128-134, 2010.Data files:
References- [1] F. L. Lizzi, E. J. Feleppa, S. K. Alam, and C. X. Deng, “Ultrasonic spectrum analysis for tissue evaluation,” Pattern Recognition Letters, Vol.24, Issues 4-5, pp. 637-658, 2003.
- [2] D. Robinson, C. Chen, and L. Wilson, “Image matching for pulse echo measurement of ultrasonic velocity,” Image and Vision Computing, Vol.1, Issue 3, pp. 145-151, 1983.
- [3] V. Chalana and Y. Kim, “A methodology for evaluation of boundary detection algorithms on medicalimages,” IEEE Trans. Med. Imaging, Vol.16, No.5, pp. 642-52, 1997.
- [4] J. Hsu, C. Tseng, and S. Chen, “A methodology for evaluation of boundary detection algorithms onbreast ultrasound images,” J. Med. Eng. Technol., Vol.25, No.4, pp. 173-177, 2001.
- [5] http://medical.nema.org/
- [6] D. H. Ballard, , “Generalizing the Hough transform to detect arbitrary shapes,” Pattern Recognition, Vol.13, No.2, pp. 111-122, 1981.
