Computer-aided detection of bladder tumors based on the thickness mapping of bladder wall in MR images

Hongbin Zhu; Chaijie Duan; Ruirui Jiang; Lihong Li; Yi Fan; Xiaokang Yu; Wei Zeng; Xianfeng Gu; Zhengrong Liang

doi:10.1117/12.844439

12 March 2010 Computer-aided detection of bladder tumors based on the thickness mapping of bladder wall in MR images

Hongbin Zhu, Chaijie Duan, Ruirui Jiang, Lihong Li, Yi Fan, Xiaokang Yu, Wei Zeng, Xianfeng Gu, Zhengrong Liang

Proceedings Volume 7623, Medical Imaging 2010: Image Processing; 76234H (2010) https://doi.org/10.1117/12.844439
Event: SPIE Medical Imaging, 2010, San Diego, California, United States

Abstract

Bladder cancer is reported to be the fifth leading cause of cancer deaths in the United States. Recent advances in medical imaging technologies, such as magnetic resonance (MR) imaging, make virtual cystoscopy a potential alternative with advantages as being a safe and non-invasive method for evaluation of the entire bladder and detection of abnormalities. To help reducing the interpretation time and reading fatigue of the readers or radiologists, we introduce a computer-aided detection scheme based on the thickness mapping of the bladder wall since locally-thickened bladder wall often appears around tumors. In the thickness mapping method, the path used to measure the thickness can be determined without any ambiguity by tracing the gradient direction of the potential field between the inner and outer borders of the bladder wall. The thickness mapping of the three-dimensional inner border surface of the bladder is then flattened to a twodimensional (2D) gray image with conformal mapping method. In the 2D flattened image, a blob detector is applied to detect the abnormalities, which are actually the thickened bladder wall indicating bladder lesions. Such scheme was tested on two MR datasets, one from a healthy volunteer and the other from a patient with a tumor. The result is preliminary, but very promising with 100% detection sensitivity at 7 FPs per case.

Citation Download Citation

Hongbin Zhu, Chaijie Duan, Ruirui Jiang, Lihong Li, Yi Fan, Xiaokang Yu, Wei Zeng, Xianfeng Gu, and Zhengrong Liang "Computer-aided detection of bladder tumors based on the thickness mapping of bladder wall in MR images", Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 76234H (12 March 2010); https://doi.org/10.1117/12.844439

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