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Automated Prostate Cancer Detection on Multi-parametric MR imaging via Texture Analysis
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 Title & Authors
Automated Prostate Cancer Detection on Multi-parametric MR imaging via Texture Analysis
Kim, YoungGi; Jung, Julip; Hong, Helen; Hwang, Sung Il;
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 Abstract
In this paper, we propose an automatic prostate cancer detection method using position, signal intensity and texture feature based on SVM in multi-parametric MR images. First, to align the prostate on DWI and ADC map to T2wMR, the transformation parameters of DWI are estimated by normalized mutual information-based rigid registration. Then, to normalize the signal intensity range among inter-patient images, histogram stretching is performed. Second, to detect prostate cancer areas in T2wMR, SVM classification with position, signal intensity and texture features was performed on T2wMR, DWI and ADC map. Our feature classification using multi-parametric MR imaging can improve the prostate cancer detection rate on T2wMR.
 Keywords
Multi-parametric MRI;Prostate Cancer Detection;Texture Analysis;Support Vector Machine;
 Language
Korean
 Cited by
1.
복부 컴퓨터단층촬영 영상에서 다중 아틀라스 기반 위치적 정보를 사용한 계층적 장기 분할,김현진;김현아;이한상;홍헬렌;

한국멀티미디어학회논문지, 2016. vol.19. 12, pp.1960-1969 crossref(new window)
1.
Hierarchical Organ Segmentation using Location Information based on Multi-atlas in Abdominal CT Images, Journal of Korea Multimedia Society, 2016, 19, 12, 1960  crossref(new windwow)
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