Prostate cancer detection in dynamic MRIs

Chuan Yu Chang, Hui Ya Hu, Yuh Shyan Tsai

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

12 Citations (Scopus)

Abstract

In Taiwan, occurrence rate of prostate cancer has been going up over the past few decades. In order to help urologists to detect prostate cancer, a prostate cancer detection system in dynamic MRIs is proposed in this paper. Dynamic MRIs are commonly used for auxiliary tool in clinical study and helpful for diagnosing prostate cancer. Firstly, an ACM (Active Contour Model) is trained and used to segment the prostate. Secondly, 136 features are extracted from the dynamic MRIs after injection at different time (0, 20, 60 and 100 second respectively) and transformed them into RIC curves. Thirdly, 10 discriminative features are selected by FDR (Fisher's Discrimination Ration) and SFFS (Sequential Forward Floating Selection). Finally, the SVM classifier is adopted to classify the segmented prostate into two categories: tumor and normal. Experimental results showed that the accuracy of the proposed method is up to 94.7493%.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Digital Signal Processing, DSP 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1279-1282
Number of pages4
ISBN (Electronic)9781479980581, 9781479980581
DOIs
Publication statusPublished - 2015 Sept 9
EventIEEE International Conference on Digital Signal Processing, DSP 2015 - Singapore, Singapore
Duration: 2015 Jul 212015 Jul 24

Publication series

NameInternational Conference on Digital Signal Processing, DSP
Volume2015-September

Conference

ConferenceIEEE International Conference on Digital Signal Processing, DSP 2015
Country/TerritorySingapore
CitySingapore
Period15-07-2115-07-24

All Science Journal Classification (ASJC) codes

  • Signal Processing

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