title: Computer-aided Detection of Prostate Cancer with MRI: Technology and Applications.
abstract: One in six men will develop prostate cancer in his lifetime. Early detection and accurate diagnosis of the disease can improve cancer survival and reduce treatment costs. Recently, imaging of prostate cancer has greatly advanced since the introduction of multiparametric magnetic resonance imaging (mp-MRI). Mp-MRI consists of T2-weighted sequences combined with functional sequences including dynamic contrast-enhanced MRI, diffusion-weighted MRI, and magnetic resonance spectroscopy imaging. Because of the big data and variations in imaging sequences, detection can be affected by multiple factors such as observer variability and visibility and complexity of the lesions. To improve quantitative assessment of the disease, various computer-aided detection systems have been designed to help radiologists in their clinical practice. This review paper presents an overview of literatures on computer-aided detection of prostate cancer with mp-MRI, which include the technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application.
authors.affiliation: Department of Radiology and Imaging Sciences, Emory University School of Medicine, 1841 Clifton Road NE, Atlanta, GA 30329; Center of Medical Imaging and Image-guided Therapy, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, China.
authors.forename: Lizhi
authors.initials: L
authors.lastname: Liu
authors.affiliation: Department of Radiology and Imaging Sciences, Emory University School of Medicine, 1841 Clifton Road NE, Atlanta, GA 30329.
authors.forename: Zhiqiang
authors.initials: Z
authors.lastname: Tian
authors.affiliation: Center of Medical Imaging and Image-guided Therapy, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, 510060, China.
authors.forename: Zhenfeng
authors.initials: Z
authors.lastname: Zhang
authors.affiliation: Department of Radiology and Imaging Sciences, Emory University School of Medicine, 1841 Clifton Road NE, Atlanta, GA 30329; Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, 1841 Clifton Road NE, Atlanta, Georgia 30329; Winship Cancer Institute of Emory University, 1841 Clifton Road NE, Atlanta, Georgia 30329. Electronic address: bfei@emory.edu.
authors.forename: Baowei
authors.initials: B
authors.lastname: Fei
mesh_terms: D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D011467:Prostate / Q000000981:diagnostic imaging / Q000473:pathology; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology
keywords: MR imaging; Prostate cancer; computer-aided detection; image quantification