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Computer Aided-Diagnosis of Prostate Cancer on Multiparametric MRI: A Technical Review of Current Research

Prostate cancer (PCa) is the most commonly diagnosed cancer among men in the United States. In this paper, we survey computer aided-diagnosis (CADx) systems that use multiparametric magnetic resonance imaging (MP-MRI) for detection and diagnosis of prostate cancer. We review and list mainstream tech...

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Autores principales: Wang, Shijun, Burtt, Karen, Turkbey, Baris, Choyke, Peter, Summers, Ronald M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4267002/
https://www.ncbi.nlm.nih.gov/pubmed/25525604
http://dx.doi.org/10.1155/2014/789561
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author Wang, Shijun
Burtt, Karen
Turkbey, Baris
Choyke, Peter
Summers, Ronald M.
author_facet Wang, Shijun
Burtt, Karen
Turkbey, Baris
Choyke, Peter
Summers, Ronald M.
author_sort Wang, Shijun
collection PubMed
description Prostate cancer (PCa) is the most commonly diagnosed cancer among men in the United States. In this paper, we survey computer aided-diagnosis (CADx) systems that use multiparametric magnetic resonance imaging (MP-MRI) for detection and diagnosis of prostate cancer. We review and list mainstream techniques that are commonly utilized in image segmentation, registration, feature extraction, and classification. The performances of 15 state-of-the-art prostate CADx systems are compared through the area under their receiver operating characteristic curves (AUC). Challenges and potential directions to further the research of prostate CADx are discussed in this paper. Further improvements should be investigated to make prostate CADx systems useful in clinical practice.
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spelling pubmed-42670022014-12-18 Computer Aided-Diagnosis of Prostate Cancer on Multiparametric MRI: A Technical Review of Current Research Wang, Shijun Burtt, Karen Turkbey, Baris Choyke, Peter Summers, Ronald M. Biomed Res Int Review Article Prostate cancer (PCa) is the most commonly diagnosed cancer among men in the United States. In this paper, we survey computer aided-diagnosis (CADx) systems that use multiparametric magnetic resonance imaging (MP-MRI) for detection and diagnosis of prostate cancer. We review and list mainstream techniques that are commonly utilized in image segmentation, registration, feature extraction, and classification. The performances of 15 state-of-the-art prostate CADx systems are compared through the area under their receiver operating characteristic curves (AUC). Challenges and potential directions to further the research of prostate CADx are discussed in this paper. Further improvements should be investigated to make prostate CADx systems useful in clinical practice. Hindawi Publishing Corporation 2014 2014-12-01 /pmc/articles/PMC4267002/ /pubmed/25525604 http://dx.doi.org/10.1155/2014/789561 Text en Copyright © 2014 Shijun Wang et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review Article
Wang, Shijun
Burtt, Karen
Turkbey, Baris
Choyke, Peter
Summers, Ronald M.
Computer Aided-Diagnosis of Prostate Cancer on Multiparametric MRI: A Technical Review of Current Research
title Computer Aided-Diagnosis of Prostate Cancer on Multiparametric MRI: A Technical Review of Current Research
title_full Computer Aided-Diagnosis of Prostate Cancer on Multiparametric MRI: A Technical Review of Current Research
title_fullStr Computer Aided-Diagnosis of Prostate Cancer on Multiparametric MRI: A Technical Review of Current Research
title_full_unstemmed Computer Aided-Diagnosis of Prostate Cancer on Multiparametric MRI: A Technical Review of Current Research
title_short Computer Aided-Diagnosis of Prostate Cancer on Multiparametric MRI: A Technical Review of Current Research
title_sort computer aided-diagnosis of prostate cancer on multiparametric mri: a technical review of current research
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4267002/
https://www.ncbi.nlm.nih.gov/pubmed/25525604
http://dx.doi.org/10.1155/2014/789561
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