Genetic programming for tuberculosis screening from raw X-ray images

Created by W.Langdon from gp-bibliography.bib Revision:1.4504

  author =       "Armand R. Burks and William F. Punch",
  title =        "Genetic programming for tuberculosis screening from
                 raw {X-ray} images",
  booktitle =    "GECCO '18: Proceedings of the Genetic and Evolutionary
                 Computation Conference",
  year =         "2018",
  editor =       "Hernan Aguirre and Keiki Takadama and 
                 Hisashi Handa and Arnaud Liefooghe and Tomohiro Yoshikawa and 
                 Andrew M. Sutton and Satoshi Ono and Francisco Chicano and 
                 Shinichi Shirakawa and Zdenek Vasicek and 
                 Roderich Gross and Andries Engelbrecht and Emma Hart and 
                 Sebastian Risi and Ekart Aniko and Julian Togelius and 
                 Sebastien Verel and Christian Blum and Will Browne and 
                 Yusuke Nojima and Tea Tusar and Qingfu Zhang and 
                 Nikolaus Hansen and Jose Antonio Lozano and 
                 Dirk Thierens and Tian-Li Yu and Juergen Branke and 
                 Yaochu Jin and Sara Silva and Hitoshi Iba and 
                 Anna I Esparcia-Alcazar and Thomas Bartz-Beielstein and 
                 Federica Sarro and Giuliano Antoniol and Anne Auger and 
                 Per Kristian Lehre",
  isbn13 =       "978-1-4503-5618-3",
  pages =        "1214--1221",
  address =      "Kyoto, Japan",
  DOI =          "doi:10.1145/3205455.3205461",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  month =        "15-19 " # jul,
  organisation = "SIGEVO",
  keywords =     "genetic algorithms, genetic programming",
  abstract =     "Genetic programming has been successfully applied to
                 several real-world problem domains. One such
                 application area is image classification, wherein
                 genetic programming has been used for a variety of
                 problems such as breast cancer detection, face
                 detection, and pedestrian detection, to name a few. We
                 present the use of genetic programming for detecting
                 active tuberculosis in raw X-ray images. Our results
                 demonstrate that genetic programming evolves
                 classifiers that achieve promising accuracy results
                 compared to that of traditional image classification
                 techniques. Our classifiers do not require
                 pre-processing, segmentation, or feature extraction
                 beforehand. Furthermore, our evolved classifiers
                 process a raw X-ray image and return a classification
                 orders of magnitude faster than the reported times for
                 traditional techniques.",
  notes =        "Also known as \cite{3205461} GECCO-2018 A
                 Recombination of the 27th International Conference on
                 Genetic Algorithms (ICGA-2018) and the 23rd Annual
                 Genetic Programming Conference (GP-2018)",

Genetic Programming entries for Armand R Burks William F Punch