{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T14:10:07Z","timestamp":1766067007619,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":51,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,7,13]],"date-time":"2019-07-13T00:00:00Z","timestamp":1562976000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,7,13]]},"DOI":"10.1145\/3319619.3326864","type":"proceedings-article","created":{"date-parts":[[2019,7,10]],"date-time":"2019-07-10T12:10:59Z","timestamp":1562760659000},"page":"1837-1845","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["Semantic learning machine improves the CNN-Based detection of prostate cancer in non-contrast-enhanced MRI"],"prefix":"10.1145","author":[{"given":"Paulo","family":"Lapa","sequence":"first","affiliation":[{"name":"Universidade Nova de Lisboa, Lisboa, Portugal"}]},{"given":"Ivo","family":"Gon\u00e7alves","sequence":"additional","affiliation":[{"name":"University of Coimbra, Coimbra, Portugal"}]},{"given":"Leonardo","family":"Rundo","sequence":"additional","affiliation":[{"name":"University of Cambridge, Cambridge, UK"}]},{"given":"Mauro","family":"Castelli","sequence":"additional","affiliation":[{"name":"Universidade Nova de Lisboa, Lisboa, Portugal"}]}],"member":"320","published-online":{"date-parts":[[2019,7,13]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Mart\u00edn Abadi Paul Barham Jianmin Chen Zhifeng Chen Andy Davis Jeffrey Dean Matthieu Devin Sanjay Ghemawat Geoffrey Irving Michael Isard etal 2015. TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems. https:\/\/www.tensorflow.org\/ Software available from tensorflow.org.  Mart\u00edn Abadi Paul Barham Jianmin Chen Zhifeng Chen Andy Davis Jeffrey Dean Matthieu Devin Sanjay Ghemawat Geoffrey Irving Michael Isard et al. 2015. TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems. https:\/\/www.tensorflow.org\/ Software available from tensorflow.org."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1117\/1.JMI.5.4.044501"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-7908-2604-3_16"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0262-8856(98)00166-8"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1148\/rg.271065078"},{"key":"e_1_3_2_1_6_1","unstructured":"Fran\u00e7ois Chollet et al. 2015. Keras. https:\/\/keras.io.  Fran\u00e7ois Chollet et al. 2015. Keras. https:\/\/keras.io."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-013-9622-7"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1117\/1.JMI.4.4.041307"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2016.04.010"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.3389\/fninf.2014.00008"},{"volume-title":"Genetic Programming","author":"Gon\u00e7alves Ivo","key":"e_1_3_2_1_11_1","unstructured":"Ivo Gon\u00e7alves , Sara Silva , and Carlos M Fonseca . 2015. On the generalization ability of geometric semantic genetic programming . In Genetic Programming . Springer , 41--52. Ivo Gon\u00e7alves, Sara Silva, and Carlos M Fonseca. 2015. On the generalization ability of geometric semantic genetic programming. In Genetic Programming. Springer, 41--52."},{"key":"e_1_3_2_1_12_1","volume-title":"Fonseca","author":"Gon\u00e7alves Ivo","year":"2015","unstructured":"Ivo Gon\u00e7alves , Sara Silva , and Carlos M . Fonseca . 2015 . Semantic learning machine: a feedforward neural network construction algorithm inspired by geometric semantic genetic programming. In Progress in Artificial Intelligence. Lecture Notes in Computer Science, Vol. 9273 . Springer , 280--285. Ivo Gon\u00e7alves, Sara Silva, and Carlos M. Fonseca. 2015. Semantic learning machine: a feedforward neural network construction algorithm inspired by geometric semantic genetic programming. In Progress in Artificial Intelligence. Lecture Notes in Computer Science, Vol. 9273. Springer, 280--285."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/2908961.2908988"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3071178.3071328"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1474-4422(17)30158-8"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2015.2508280"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.07.2211"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.12111634"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3205651.3205778"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.09.084"},{"key":"e_1_3_2_1_22_1","volume-title":"Michael Rieger, and Udo Nagele.","author":"Junker Daniel","year":"2018","unstructured":"Daniel Junker , Fabian Steinkohl , Veronika Fritz , Jasmin Bektic , Theodoros Tokas , Friedrich Aigner , Thomas RW Herrmann , Michael Rieger, and Udo Nagele. 2018 . Comparison of multiparametric and biparametric MRI of the prostate: are gadolinium-based contrast agents needed for routine examinations? World J. Urol . (2018), 1--9. Daniel Junker, Fabian Steinkohl, Veronika Fritz, Jasmin Bektic, Theodoros Tokas, Friedrich Aigner, Thomas RW Herrmann, Michael Rieger, and Udo Nagele. 2018. Comparison of multiparametric and biparametric MRI of the prostate: are gadolinium-based contrast agents needed for routine examinations? World J. Urol. (2018), 1--9."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2016.10.004"},{"key":"e_1_3_2_1_24_1","volume-title":"Adam: a method for stochastic optimization.arXiv preprint arXiv:1412.6980","author":"Kingma Diederik P","year":"2014","unstructured":"Diederik P Kingma and Jimmy Ba. 2014. Adam: a method for stochastic optimization.arXiv preprint arXiv:1412.6980 ( 2014 ). Diederik P Kingma and Jimmy Ba. 2014. Adam: a method for stochastic optimization.arXiv preprint arXiv:1412.6980 (2014)."},{"key":"e_1_3_2_1_25_1","first-page":"034502","article-title":"Classification of suspicious lesions on prostate multiparametric MRI using machine learning","volume":"5","author":"Kwon Deukwoo","year":"2018","unstructured":"Deukwoo Kwon , Isildinha M Reis , Adrian L Breto , Yohann Tschudi , Nicole Gautney , Olmo Zavala-Romero , Christopher Lopez , John C Ford , Sanoj Pun-nen, Alan Pollack , 2018 . Classification of suspicious lesions on prostate multiparametric MRI using machine learning . J. Med. Imaging 5 , 3 (2018), 034502 . Deukwoo Kwon, Isildinha M Reis, Adrian L Breto, Yohann Tschudi, Nicole Gautney, Olmo Zavala-Romero, Christopher Lopez, John C Ford, Sanoj Pun-nen, Alan Pollack, et al. 2018. Classification of suspicious lesions on prostate multiparametric MRI using machine learning. J. Med. Imaging 5, 3 (2018), 034502.","journal-title":"J. Med. Imaging"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2015.02.009"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41391-017-0007-8"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2014.2303821"},{"key":"e_1_3_2_1_29_1","volume-title":"The Cancer Imaging Archive. https:\/\/wiki.cancerimagingarchive.net\/display\/Public\/SPIE-AAPM-NCI+PROSTATEx+Challenges. Online","author":"Litjens Geert","year":"2019","unstructured":"Geert Litjens , Oscar Debats , Jelle Barentsz , Nico Karssemeijer , and Henkjan Huisman . 2017. \"PROSTAT Ex Challenge data\" , The Cancer Imaging Archive. https:\/\/wiki.cancerimagingarchive.net\/display\/Public\/SPIE-AAPM-NCI+PROSTATEx+Challenges. Online ; Accessed on January 25, 2019 . Geert Litjens, Oscar Debats, Jelle Barentsz, Nico Karssemeijer, and Henkjan Huisman. 2017. \"PROSTATEx Challenge data\", The Cancer Imaging Archive. https:\/\/wiki.cancerimagingarchive.net\/display\/Public\/SPIE-AAPM-NCI+PROSTATEx+Challenges. Online; Accessed on January 25, 2019."},{"volume-title":"Medical Imaging 2017: Computer-Aided Diagnosis (Proceedings SPIE)","author":"Liu Saifeng","key":"e_1_3_2_1_30_1","unstructured":"Saifeng Liu , Huaixiu Zheng , Yesu Feng , and Wei Li. 2017. Prostate cancer diagnosis using deep learning with 3D multiparametric MRI . In Medical Imaging 2017: Computer-Aided Diagnosis (Proceedings SPIE) , Vol. 10134 . International Society for Optics and Photonics , 1013428. Saifeng Liu, Huaixiu Zheng, Yesu Feng, and Wei Li. 2017. Prostate cancer diagnosis using deep learning with 3D multiparametric MRI. In Medical Imaging 2017: Computer-Aided Diagnosis (Proceedings SPIE), Vol. 10134. International Society for Optics and Photonics, 1013428."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/42.563664"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.24487"},{"volume-title":"V-Net: fully convolutional neural networks for volumetric medical image segmentation.In Proceedings of the International Conference on 3D Vision (3DV)","author":"Milletari Fausto","key":"e_1_3_2_1_33_1","unstructured":"Fausto Milletari , Nassir Navab , and Seyed-Ahmad Ahmadi . 2016. V-Net: fully convolutional neural networks for volumetric medical image segmentation.In Proceedings of the International Conference on 3D Vision (3DV) . IEEE , 565--571. Fausto Milletari, Nassir Navab, and Seyed-Ahmad Ahmadi. 2016. V-Net: fully convolutional neural networks for volumetric medical image segmentation.In Proceedings of the International Conference on 3D Vision (3DV). IEEE, 565--571."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-32937-1_3"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/2463372.2463492"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.12.10173"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.3390\/info8020049"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2017.03.011"},{"key":"e_1_3_2_1_40_1","volume-title":"Salvatore Vitabile, Giancarlo Mauri, Daniela Besozzi, and Carmelo Militello.","author":"Rundo Leonardo","year":"2019","unstructured":"Leonardo Rundo , Andrea Tangherloni , Paolo Cazzaniga , Marco S Nobile , Giorgio Russo , Maria Carla Gilardi , Salvatore Vitabile, Giancarlo Mauri, Daniela Besozzi, and Carmelo Militello. 2019 . A novel framework for MR image segmentation and quantification by using MedGA. Comput. Methods Programs Biomed. (2019). In press . Leonardo Rundo, Andrea Tangherloni, Paolo Cazzaniga, Marco S Nobile, Giorgio Russo, Maria Carla Gilardi, Salvatore Vitabile, Giancarlo Mauri, Daniela Besozzi, and Carmelo Militello. 2019. A novel framework for MR image segmentation and quantification by using MedGA. Comput. Methods Programs Biomed. (2019). In press."},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/SSCI.2016.7850261"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2018.11.013"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1002\/widm.1248"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21551"},{"key":"e_1_3_2_1_45_1","volume-title":"Proceedings of the International Conference on Learning Representations (ICLR). arXiv preprint arXiv:1409","author":"Simonyan Karen","year":"2015","unstructured":"Karen Simonyan and Andrew Zisserman . 2015 . Very deep convolutional networks for large-scale image recognition . In Proceedings of the International Conference on Learning Representations (ICLR). arXiv preprint arXiv:1409 .1556. Karen Simonyan and Andrew Zisserman. 2015. Very deep convolutional networks for large-scale image recognition. In Proceedings of the International Conference on Learning Representations (ICLR). arXiv preprint arXiv:1409.1556."},{"key":"e_1_3_2_1_46_1","volume-title":"Proceedings of the International Conference on Learning Representations (ICLR). 1--14","author":"Springenberg Jost Tobias","year":"2014","unstructured":"Jost Tobias Springenberg , Alexey Dosovitskiy , Thomas Brox , and Martin Ried-miller. 2014 . Striving for simplicity: The all convolutional net . In Proceedings of the International Conference on Learning Representations (ICLR). 1--14 . arXiv preprint arXiv:1412.6806. Jost Tobias Springenberg, Alexey Dosovitskiy, Thomas Brox, and Martin Ried-miller. 2014. Striving for simplicity: The all convolutional net. In Proceedings of the International Conference on Learning Representations (ICLR). 1--14. arXiv preprint arXiv:1412.6806."},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.21037\/tcr.2016.06.20"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1117\/1.JMI.5.4.044507"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-67389-9_26"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21333"},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2017.2789181"},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1109\/4235.585893"}],"event":{"name":"GECCO '19: Genetic and Evolutionary Computation Conference","sponsor":["SIGEVO ACM Special Interest Group on Genetic and Evolutionary Computation"],"location":"Prague Czech Republic","acronym":"GECCO '19"},"container-title":["Proceedings of the Genetic and Evolutionary Computation Conference Companion"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3319619.3326864","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3319619.3326864","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T00:25:34Z","timestamp":1750206334000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3319619.3326864"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,13]]},"references-count":51,"alternative-id":["10.1145\/3319619.3326864","10.1145\/3319619"],"URL":"https:\/\/doi.org\/10.1145\/3319619.3326864","relation":{},"subject":[],"published":{"date-parts":[[2019,7,13]]},"assertion":[{"value":"2019-07-13","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}