Enhancing classification performance of convolutional neural networks for prostate cancer detection on magnetic resonance images: a study with the semantic learning machine

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Lapa:2019:GECCOcomp,

• author = "Paulo Lapa and Ivo Goncalves and Leonardo Rundo and Mauro Castelli",
• title = "Enhancing classification performance of convolutional neural networks for prostate cancer detection on magnetic resonance images: a study with the semantic learning machine",
• booktitle = "GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion",
• year = "2019",
• editor = "Richard Allmendinger and Carlos Cotta and Carola Doerr and Pietro S. Oliveto and Thomas Weise and Ales Zamuda and Anne Auger and Dimo Brockhoff and Nikolaus Hansen and Tea Tusar and Konstantinos Varelas and David Camacho-Fernandez and Massimiliano Vasile and Annalisa Riccardi and Bilel Derbel and Ke Li and Xiaodong Li and Saul Zapotecas and Qingfu Zhang and Ozgur Akman and Khulood Alyahya and Juergen Branke and Jonathan Fieldsend and Tinkle Chugh and Jussi Hakanen and Josu {Ceberio Uribe} and Valentino Santucci and Marco Baioletti and John McCall and Emma Hart and Daniel R. Tauritz and John R. Woodward and Koichi Nakayama and Chika Oshima and Stefan Wagner and Michael Affenzeller and Eneko Osaba and Javier {Del Ser} and Pascal Kerschke and Boris Naujoks and Vanessa Volz and Anna I Esparcia-Alcazar and Riyad Alshammari and Erik Hemberg and Tokunbo Makanju and Brad Alexander and Saemundur O. Haraldsson and Markus Wagner and Silvino {Fernandez Alzueta} and Pablo {Valledor Pellicer} and Thomas Stuetzle and David Walker and Matt Johns and Nick Ross and Ed Keedwell and Masaya Nakata and Anthony Stein and Takato Tatsumi and Nadarajen Veerapen and Arnaud Liefooghe and Sebastien Verel and Gabriela Ochoa and Stephen Smith and Stefano Cagnoni and Robert M. Patton and William {La Cava} and Randal Olson and Patryk Orzechowski and Ryan Urbanowicz and Akira Oyama and Koji Shimoyama and Hemant Kumar Singh and Kazuhisa Chiba and Pramudita Satria Palar and Alma Rahat and Richard Everson and Handing Wang and Yaochu Jin and Marcus Gallagher and Mike Preuss and Olivier Teytaud and Fernando Lezama and Joao Soares and Zita Vale",
• isbn13 = "978-1-4503-6748-6",
• pages = "381--382",
• address = "Prague, Czech Republic",
• DOI = "doi:10.1145/3319619.3322035",
• publisher = "ACM",
• publisher_address = "New York, NY, USA",
• month = "13-17 " # jul,
• organisation = "SIGEVO",
• keywords = "genetic algorithms, genetic programming",
• abstract = "Prostate cancer (PCa) is the most common oncological disease in Western men. Even though a significant effort has been carried out by the scientific community, accurate and reliable automated PCa detection methods are still a compelling issue. In this clinical scenario, high-resolution multiparametric Magnetic Resonance Imaging (MRI) is becoming the most used modality, also enabling quantitative studies. Recently, deep learning techniques have achieved outstanding results in prostate MRI analysis tasks, in particular with regard to image classification. This paper studies the feasibility of using the Semantic Learning Machine (SLM) neuroevolution algorithm to replace the fully-connected architecture commonly used in the last layers of Convolutional Neural Networks (CNNs). The experimental phase considered the PROSTATEx dataset composed of multispectral MRI sequences. The achieved results show that, on the same non-contrast-enhanced MRI series, SLM outperforms with statistical significance a state-of-the-art CNN trained with backpropagation. The SLM performance is achieved without pre-training the underlying CNN with backpropagation. Furthermore, on average the SLM training time is approximately 14 times faster than the backpropagation-based approach.",
• notes = "Also known as \cite{3322035} GECCO-2019 A Recombination of the 28th International Conference on Genetic Algorithms (ICGA) and the 24th Annual Genetic Programming Conference (GP)",

}

Genetic Programming entries for Paulo Lapa Ivo Goncalves Leonardo Rundo Mauro Castelli

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