U-Net Architectures for Prostate Cancer Radiation Therapy: A Literature Review

<!DOCTYPE html> <html lang="en" xml:lang="en"> <head> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <title> U-Net Architectures for Prostate Cancer Radiation Therapy: A Literature Review | U.Porto Journal of Engineering </title> <link rel="icon" href="https://journalengineering.fe.up.pt/public/journals/3/favicon_en_US.png"> <meta name="generator" content="Open Journal Systems 3.4.0.3"> <link rel="schema.DC" href="http://purl.org/dc/elements/1.1/" /> <meta name="DC.Creator.PersonalName" content="Bruno Mendes"/> <meta name="DC.Creator.PersonalName" content="In锚s Domingues"/> <meta name="DC.Creator.PersonalName" content="Jo茫o Santos"/> <meta name="DC.Date.created" scheme="ISO8601" content="2023-01-23"/> <meta name="DC.Date.dateSubmitted" scheme="ISO8601" content="2022-04-25"/> <meta name="DC.Date.issued" scheme="ISO8601" content="2023-01-23"/> <meta name="DC.Date.modified" scheme="ISO8601" content="2023-01-23"/> <meta name="DC.Description" xml:lang="en" content="Prostate Cancer (PCa) was first diagnosed in 1853 as cirrhosis of the prostate gland. Silently asymptomatic, PCa is usually diagnosed with Digital Rectal Examination (DRE) and Prostate Specific Antigen (PSA) levels. Since the first treatment of an advanced prostatic malignancy with X-rays by Imbert and Imbert in 1904, External Beam Radiation Therapy (EBRT) is now a curative option for localised and locally advanced disease and a palliative option for the metastatic low-volume disease. With the introduction of computers in EBRT and better imaging techniques, volume delineation is still a very time-consuming task. While Deep Learning methods are urged, EBRT systems still rely on manual or semi-automatic segmentation techniques. The U-Net architecture was specially designed for medical image segmentation presenting promising results. This literature review gathers work using U-Net architectures, outlining methods, techniques and obtained outcomes as a potential foundation for an automated segmentation framework for PCa."/> <meta name="DC.Format" scheme="IMT" content="application/pdf"/> <meta name="DC.Identifier" content="2183-6493_009-001_001551"/> <meta name="DC.Identifier.pageNumber" content="177-190"/> <meta name="DC.Identifier.DOI" content="10.24840/2183-6493_009-001_001551"/> <meta name="DC.Identifier.URI" content="https://journalengineering.fe.up.pt/index.php/upjeng/article/view/2183-6493_009-001_001551"/> <meta name="DC.Language" scheme="ISO639-1" content="en"/> <meta name="DC.Rights" content="Copyright (c) 2022 Bruno Mendes, In锚s Domingues, Jo茫o Santos"/> <meta name="DC.Rights" content="https://creativecommons.org/licenses/by/4.0"/> <meta name="DC.Source" content="U.Porto Journal of Engineering"/> <meta name="DC.Source.ISSN" content="2183-6493"/> <meta name="DC.Source.Issue" content="1"/> <meta name="DC.Source.Volume" content="9"/> <meta name="DC.Source.URI" content="https://journalengineering.fe.up.pt/index.php/upjeng"/> <meta name="DC.Subject" xml:lang="en" content="U-Net"/> <meta name="DC.Subject" xml:lang="en" content="Prostate Cancer"/> <meta name="DC.Subject" xml:lang="en" content="Segmentation"/> <meta name="DC.Subject" xml:lang="en" content="Radiation therapy"/> <meta name="DC.Title" content="U-Net Architectures for Prostate Cancer Radiation Therapy: A Literature Review"/> <meta name="DC.Type" content="Text.Serial.Journal"/> <meta name="DC.Type.articleType" content="PEC202122_02"/> <meta name="gs_meta_revision" content="1.1"/> <meta name="citation_journal_title" content="U.Porto Journal of Engineering"/> <meta name="citation_journal_abbrev" content="UPjeng"/> <meta name="citation_issn" content="2183-6493"/> <meta name="citation_author" content="Bruno Mendes"/> <meta name="citation_author_institution" content="Universidade do Porto : Faculdade de Engenharia"/> <meta name="citation_author" content="In锚s Domingues"/> <meta name="citation_author_institution" content="Polit茅cnico de Coimbra"/> <meta name="citation_author" content="Jo茫o Santos"/> <meta name="citation_author_institution" content="Centro de Investiga莽茫o do Instituto Portugu锚s de Oncologia do Porto (CI-IPOP)"/> <meta name="citation_title" content="U-Net Architectures for Prostate Cancer Radiation Therapy: A Literature Review"/> <meta name="citation_language" content="en"/> <meta name="citation_date" content="2023/01/23"/> <meta name="citation_volume" content="9"/> <meta name="citation_issue" content="1"/> <meta name="citation_firstpage" content="177"/> <meta name="citation_lastpage" content="190"/> <meta name="citation_doi" content="10.24840/2183-6493_009-001_001551"/> <meta name="citation_abstract_html_url" content="https://journalengineering.fe.up.pt/index.php/upjeng/article/view/2183-6493_009-001_001551"/> <meta name="citation_abstract" xml:lang="en" content="Prostate Cancer (PCa) was first diagnosed in 1853 as cirrhosis of the prostate gland. Silently asymptomatic, PCa is usually diagnosed with Digital Rectal Examination (DRE) and Prostate Specific Antigen (PSA) levels. Since the first treatment of an advanced prostatic malignancy with X-rays by Imbert and Imbert in 1904, External Beam Radiation Therapy (EBRT) is now a curative option for localised and locally advanced disease and a palliative option for the metastatic low-volume disease. With the introduction of computers in EBRT and better imaging techniques, volume delineation is still a very time-consuming task. While Deep Learning methods are urged, EBRT systems still rely on manual or semi-automatic segmentation techniques. The U-Net architecture was specially designed for medical image segmentation presenting promising results. This literature review gathers work using U-Net architectures, outlining methods, techniques and obtained outcomes as a potential foundation for an automated segmentation framework for PCa."/> <meta name="citation_keywords" xml:lang="en" content="U-Net"/> <meta name="citation_keywords" xml:lang="en" content="Prostate Cancer"/> <meta name="citation_keywords" xml:lang="en" content="Segmentation"/> <meta name="citation_keywords" xml:lang="en" content="Radiation therapy"/> <meta name="citation_pdf_url" content="https://journalengineering.fe.up.pt/index.php/upjeng/article/download/2183-6493_009-001_001551/743"/> <link rel="alternate" type="application/atom+xml" href="https://journalengineering.fe.up.pt/index.php/upjeng/gateway/plugin/APP%5Cplugins%5Cgeneric%5CwebFeed%5CWebFeedGatewayPlugin/atom"> <link rel="alternate" type="application/rdf+xml" href="https://journalengineering.fe.up.pt/index.php/upjeng/gateway/plugin/APP%5Cplugins%5Cgeneric%5CwebFeed%5CWebFeedGatewayPlugin/rss"> <link rel="alternate" type="application/rss+xml" href="https://journalengineering.fe.up.pt/index.php/upjeng/gateway/plugin/APP%5Cplugins%5Cgeneric%5CwebFeed%5CWebFeedGatewayPlugin/rss2"> <link rel="stylesheet" href="https://journalengineering.fe.up.pt/index.php/upjeng/$$$call$$$/page/page/css?name=bootstrap" type="text/css" /> </head> <body class="pkp_page_article pkp_op_view has_site_logo"> <div class="pkp_structure_page"> <nav id="accessibility-nav" class="sr-only" role="navigation" aria-label="Quick jump to page content"> <ul> <li><a href="#main-navigation">Main Navigation</a></li> <li><a href="#main-content">Main Content</a></li> <li><a href="#sidebar">Sidebar</a></li> </ul> </nav> <header class="navbar navbar-default" id="headerNavigationContainer" role="banner"> <div class="container-fluid"> <div class="row"> <nav aria-label="User Navigation"> <ul id="navigationUser" class="nav nav-pills tab-list pull-right"> <li class=" menu-item-1"> <a href="https://journalengineering.fe.up.pt/index.php/upjeng/user/register"> Register </a> </li> <li class=" menu-item-2"> <a href="https://journalengineering.fe.up.pt/index.php/upjeng/login"> Login </a> </li> </ul> </nav> </div> </div> <div class="container-fluid"> <div class="navbar-header"> <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#nav-menu" aria-expanded="false" aria-controls="nav-menu"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar"></span> <span class="icon-bar"></span> <span class="icon-bar"></span> </button> <div class="site-name"> <a href=" https://journalengineering.fe.up.pt/index.php/upjeng/index " class="navbar-brand navbar-brand-logo"> <img src="https://journalengineering.fe.up.pt/public/journals/3/pageHeaderLogoImage_en_US.png" alt="U. 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Silently asymptomatic, PCa is usually diagnosed with Digital Rectal Examination (DRE) and Prostate Specific Antigen (PSA) levels. Since the first treatment of an advanced prostatic malignancy with X-rays by Imbert and Imbert in 1904, External Beam Radiation Therapy (EBRT) is now a curative option for localised and locally advanced disease and a palliative option for the metastatic low-volume disease. With the introduction of computers in EBRT and better imaging techniques, volume delineation is still a very time-consuming task. While Deep Learning methods are urged, EBRT systems still rely on manual or semi-automatic segmentation techniques. The U-Net architecture was specially designed for medical image segmentation presenting promising results. This literature review gathers work using U-Net architectures, outlining methods, techniques and obtained outcomes as a potential foundation for an automated segmentation framework for PCa.</p> </div> </div> <section class="item downloads_chart"> <h2 class="label"> Downloads </h2> <div class="value"> <canvas class="usageStatsGraph" data-object-type="Submission" data-object-id="1551"></canvas> <div class="usageStatsUnavailable" data-object-type="Submission" data-object-id="1551"> Download data is not yet available. </div> </div> </section> </section> <section class="article-more-details"> <h2 class="sr-only">Article Details</h2>   <div class="panel panel-default copyright"> <div class="panel-body"> <a rel="license" href="https://creativecommons.org/licenses/by/4.0/"><img alt="Creative Commons License" src="//i.creativecommons.org/l/by/4.0/88x31.png" /></a><p>This work is licensed under a <a rel="license" href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 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U-Net Architectures for Prostate Cancer Radiation Therapy: A Literature Review | U.Porto Journal of Engineering