https://m2.mtmt.hu/ eng 2026-10-24 23:02 JournalArticle 3352857 VALIDATED true 0 2018-09-26T22:20:08.000+0000 false 3352857 2026-10-20T17:03:58.071+0000 2024-11-19T05:06:56.143+0000 2018-02-01T07:45:37.000+0000 true 10025948 Pécsi Éva /api/admin/10025948 Admin true 10025948 2025-03-17T19:54:45.808+0000 2025-03-17T19:54:45.808+0000 2024-11-19T05:06:56.437+0000 true 10080073 Bolgár Andrea /api/admin/10080073 Admin true Admin 10067876 /api/admin/10067876 Ladányi Gusztáv true true Admin 10080073 /api/admin/10080073 Bolgár Andrea true true 2024-10-17T17:10:18.585+0000 true false true 24 24 /api/publicationtype/24 PublicationType 1 true 24 JournalArticle true 10000059 Article true 24 24 /api/publicationtype/24 PublicationType 1 true 24 JournalArticle /api/subtype/10000059 Szakcikk SubType 101 true 10000059 true 1 /api/category/1 Category true 1 Ribli, D Detecting and classifying lesions in mammograms with Deep Learning. true true /api/journal/10019966 REVIEWED true false 10019966 false 10019966 true 2045-2322 Journal FOREIGN 8 1 4165 4165 7 2018 In the last two decades, Computer Aided Detection (CAD) systems were developed to help radiologists analyse screening mammograms, however benefits of current CAD technologies appear to be contradictory, therefore they should be improved to be ultimately considered useful. Since 2012, deep convolutional neural networks (CNN) have been a tremendous success in image recognition, reaching human performance. These methods have greatly surpassed the traditional approaches, which are similar to currently used CAD solutions. Deep CNN-s have the potential to revolutionize medical image analysis. We propose a CAD system based on one of the most successful object detection frameworks, Faster R-CNN. The system detects and classifies malignant or benign lesions on a mammogram without any human intervention. The proposed method sets the state of the art classification performance on the public INbreast database, AUC = 0.95. The approach described here has achieved 2nd place in the Digital Mammography DREAM Challenge with AUC = 0.85. When used as a detector, the system reaches high sensitivity with very few false positive marks per image on the INbreast dataset. Source code, the trained model and an OsiriX plugin are published online at https://github.com/riblidezso/frcnn_cad . Funding 2028751 /api/funding/2028751 false true true true 2018 (Unger Zsuzsa (radiológia); 2018.03.27. 11:11:44) true true true false true false GOLD 2026-10-20 true https://doi.org/10.1038/s41598-018-22437-z 666 0 663 658 6 639 647 499 653 661 661 656 656 661 5 0 666 661 663 658 0 1 1 Folyóiratcikk Journal Article 24 489 Könyvrészlet Chapter in Book 25 172 Könyv Book 23 2 Egyéb konferenciaközlemény Conference paper 31 0 Egyéb konferenciakötet Conference proceedings 32 0 Oltalmi formák Protection forms 26 0 Disszertáció Thesis 28 0 Egyéb Miscellaneous 29 3 Alkotás Achievement 22 0 Kutatási adat Research data 33 0 Folyóiratcikk Journal Article 24 0 0 0 Könyvrészlet Chapter in Book 25 0 0 0 Könyv Book 23 0 0 0 Egyéb konferenciaközlemény Conference paper 31 0 0 0 Egyéb konferenciakötet Conference proceedings 32 0 0 0 Oltalmi formák Protection forms 26 0 0 0 Disszertáció Thesis 28 0 0 0 Egyéb Miscellaneous 29 0 0 0 Alkotás Achievement 22 0 0 0 Kutatási adat Research data 33 0 0 0 2018 0 13 13 13 13 2019 0 67 66 67 66 2020 0 94 93 94 93 2021 0 107 107 107 107 2022 0 106 105 106 105 2023 0 80 79 80 79 2024 0 67 66 67 66 2025 0 84 84 84 84 2026 0 48 48 48 48 D1 A nemzetközi true 10000521,10010935,10023835 false false false 2018-09-26T10:43:49.000+0000 2018-03-27T09:12:32.000+0000 Biológiai Fizika Tanszék (ELTE / TTK / FizCsill_I); III. Sz. Belgyógyászati Klinika (SE / AOK / K); Komplex Rendszerek Fizikája Tanszék (ELTE / TTK / FizCsill_I); MTA-ELTE Statisztikus és Biológiai Fizika Kutat... (ELTE / TTK / Fiz_I); Radiológiai és Onkoterápiás Klinika (SE / AOK / K) 5 27 5 5 0 true 10080073 10067876 Language 10002 /api/language/10002 Angol English true 2 true PersonAuthorship 85085661 /api/authorship/85085661 1 0.2 true false true Author 10059140 /api/author/10059140 Ribli Dezső true 10059140 true Ribli D true false false AuthorshipType 1 /api/authorshiptype/1 0 true 0 true false true PersonAuthorship 85085662 /api/authorship/85085662 2 0.2 false false Author 10023835 /api/author/10023835 Horváth Anna true 10023835 true Horvath A true false false AuthorshipType 1 /api/authorshiptype/1 0 true 0 true false true PersonAuthorship 85085663 /api/authorship/85085663 3 0.2 false false Author 10057901 /api/author/10057901 Unger Zsuzsa true 10057901 true Unger Z true false false AuthorshipType 1 /api/authorshiptype/1 0 true 0 true false true PersonAuthorship 85085664 /api/authorship/85085664 4 0.2 false false Author 10010935 /api/author/10010935 Pollner Péter true 10010935 true Pollner 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style="float: left" src="/frontend/resources/grid/publication-core-icon.png"> <img title="Idézőközlemény" style="float: left" src="/frontend/resources/grid/publication-citation-icon.png"> <div class="autype autype0"> <span class="author-name" mtid="10059140"><a href="/gui2/?type=authors&mode=browse&sel=10059140" target="_blank">Ribli D ✉ (<span class="authorship-author-name">Ribli Dezső</span> <span class="authorAux-mtmt"> Fizika</span>) </a> </span> <span class="author-affil"><span title="Eötvös Loránd University">ELTE</span>/<span title="Faculty of Science">ELU FoS</span>/<span title="Institute of Physics">Inst_Phys</span>/Department of Physics of Complex Systems</span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" mtid="10023835"><a href="/gui2/?type=authors&mode=browse&sel=10023835" target="_blank">Horvath A (<span class="authorship-author-name">Horváth Anna</span> <span class="authorAux-mtmt"> belgyógyászat; immunológia; onkológia</span>) </a> </span> <span class="author-affil"><span title="Semmelweis University">SU</span>/<span title="Faculty of Medicine">FM</span>/<span title="Clinical">C</span>/III. Department of Internal Medicine</span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" mtid="10057901"><a href="/gui2/?type=authors&mode=browse&sel=10057901" target="_blank">Unger Z (<span class="authorship-author-name">Unger Zsuzsa</span> <span class="authorAux-mtmt"> radiológia</span>) </a> </span> <span class="author-affil"><span title="Semmelweis University">SU</span>/<span title="Faculty of Medicine">FM</span>/<span title="Clinical">C</span>/Department of Diagnostic Radiology and Oncotherapy</span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" mtid="10010935"><a href="/gui2/?type=authors&mode=browse&sel=10010935" target="_blank">Pollner P (<span class="authorship-author-name">Pollner Péter</span> <span class="authorAux-mtmt"> Elméleti és matematikai fizika</span>) </a> </span> <span class="author-affil"><span title="Eötvös Loránd University">ELTE</span>/<span title="Faculty of Science">ELU FoS</span>/<span title="Institute of Physics">Inst_Phys</span>/MTA-ELTE Statistical and Biological Physics Research Group; <span title="Eötvös Loránd University">ELTE</span>/<span title="Faculty of Science">ELU FoS</span>/<span title="Institute of Physics">Inst_Phys</span>/Department of Biological Physics</span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" mtid="10000521"><a href="/gui2/?type=authors&mode=browse&sel=10000521" target="_blank">Csabai I (<span class="authorship-author-name">Csabai István</span> <span class="authorAux-mtmt"> Statisztikus fizika</span>) </a> </span> <span class="author-affil"><span title="Eötvös Loránd University">ELTE</span>/<span title="Faculty of Science">ELU FoS</span>/<span title="Institute of Physics">Inst_Phys</span>/Department of Physics of Complex Systems</span> </div> </div> <div class="title"><a href="/gui2/?mode=browse&params=publication;3352857" target="_blank">Detecting and classifying lesions in mammograms with Deep Learning.</a></div> <div> <span class="journal-title">SCIENTIFIC REPORTS</span> <span class="journal-issn">( <a target="_blank" href="https://portal.issn.org/resource/ISSN/2045-2322">2045-2322</a>)</span>: <span class="journal-volume">8</span> <span class="journal-issue">1</span> <span class="page"> Paper 4165. 7 p. </span> <span class="year">(2018)</span> </div> <div class="pub-footer"> <span class="language" xmlns="http://www.w3.org/1999/html">Language: English | </span> <span class="identifiers"> <span class="id identifier oa_GOLD" title=" Gold "> <a style="color:blue" title="10.1038/s41598-018-22437-z" target="_blank" href="https://doi.org/10.1038/s41598-018-22437-z"> DOI </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="000427457400001" target="_blank" href="https://www.webofscience.com/wos/woscc/full-record/000427457400001"> WoS </a> </span> <span class="id identifier oa_GREEN" title=" Green "> <a style="color:blue" title="49019" target="_blank" href="https://edit.elte.hu/handle/10831/49019"> EDIT </a> </span> <span class="id identifier oa_GREEN" title=" Green "> <a style="color:blue" title="161399" target="_blank" href="https://real.mtak.hu/161399"> REAL </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="85044231314" target="_blank" href="http://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-85044231314"> Scopus </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="29545529" target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=29545529&dopt=Abstract"> PubMed </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="2017arXiv170708401R" target="_blank" href="http://ui.adsabs.harvard.edu/abs/2017arXiv170708401R"> ADS </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="1707.08401" target="_blank" href="http://arxiv.org/abs/1707.08401"> arXiv </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="PMC5854668" target="_blank" href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5854668"> Pubmed Central </a> </span> </span> <OnlyViewableByAuthor><div class="ratings"> <div class="journal-subject">Journal subject: Scopus - Multidisciplinary&nbsp;&nbsp;&nbsp;Rank:&nbsp;D1</div> <div class="journal-subject">Committee on Sociology HASSELIX SZTB [1901-]&nbsp;&nbsp;&nbsp;A nemzetközi</div> <div class="journal-subject">Committee on Regional Studies HASSELIX RTB [1901-]&nbsp;&nbsp;&nbsp;B nemzetközi</div> </div></OnlyViewableByAuthor> <div class="publication-citation" style="margin-left: 0.5cm;"> <span title="" class="citingPub-count">Citing papers: 666</span> | Independent citation: 661 | Self citation: 5 | Unknown citation: 0 | Number of citations in WoS: 499 | Number of citations in Scopus:&nbsp;653 | WoS/Scopus assigned:&nbsp;661 | Number of citations with DOI:&nbsp;647 </div> <div class="publication-citation"> <a target="_blank" href="/api/publication?cond=citations.related;eq;3352857&sort=publishedYear,desc&sort=title"> Number of cited publications: 1 </a> </div> <div class="mtid"><span class="long-pub-mtid">Publication: 3352857</span> | <span class="status-data status-VALIDATED"> Validated </span> <span class="oldId">Old id: 3352857</span> | Core Citing | <span class="type-subtype">Journal Article ( Article ) </span> | <span class="pub-category">Scientific</span> | <span class="publication-sourceOfData">MEDLINE</span> </div> <div class="funder"> (FIEK_16-1-2016-0005) </div> <div class="notDuplums"><a target="_blank" href="/api/publication/3352857/notduplums">2 marked as not duplum</a> </div> <div class="lastModified">Last Modified: 2024.11.19. 06:06 Andrea Bolgár (MTMT ellenőrzés admin5) </div> <div class="lockedBy">Centrally managed 2024.10.17. 19:10 Gusztáv Ladányi (MTMT API user, admin) Andrea Bolgár (MTMT ellenőrzés admin5) </div> </div></div>