Prostate tumor identification in ultrasound images

Chuan Yu Chang, Meng Yu Tu, Yuh Shyan Tsai

Research output: Chapter in Book/Report/Conference proceedingConference contribution


There are various medical imaging instruments used for diagnosing prostatic diseases. Ultrasound imaging is the most widely used tool in clinical diagnosis. Urologist outlines the prostate and diagnoses lesions based on his/her experiences. This diagnostic process is subjective and heuristic. Active contour model (ACM) has been successfully applied to outline the prostate contour. However, application of ACM in outlining the contour needs to give the initial contour points manually. In this paper, an automatic prostate tumor identification system is proposed. The sequential floating forward selection (SFFS) is applied to select significant features. A support vector machine (SVM) with radial basis kernel function is used for prostate tumor identification. Experimental results showed that the proposed method achieved higher accuracy than those of other methods.

Original languageEnglish
Title of host publicationIntelligent Data analysis and Its Applications, Volume II - 1st Euro-China Conference on Intelligent Data Analysis and Applications, Proceeding
EditorsShyue-Liang Wang, Jeng-Shyang Pan, Vaclav Snasel, Emilio S. Corchado, Ajith Abraham
PublisherSpringer Verlag
Number of pages10
ISBN (Electronic)9783319077727
Publication statusPublished - 2014
Event1st Euro-China Conference on Intelligent Data Analysis and Applications, ECC 2014 - Shenzhen, China
Duration: 2014 Jun 132014 Jun 15

Publication series

NameAdvances in Intelligent Systems and Computing
ISSN (Print)2194-5357


Other1st Euro-China Conference on Intelligent Data Analysis and Applications, ECC 2014

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)


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