Machine learning methods for classifying mammographic regions using the wavelet transform and radiomic texture features

Jaider Stiven Rincón, Andrés E. Castro-Ospina, Fabián R. Narváez, Gloria M. Díaz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations
Original languageEnglish
Title of host publicationTechnology Trends - 4th International Conference, CITT 2018, Revised Selected Papers
EditorsMiguel Botto-Tobar, Mayra D’Armas, Miguel Zúñiga Sánchez, Miguel Zúñiga-Prieto, Guillermo Pizarro
PublisherSpringer Verlag
Pages617-629
Number of pages13
ISBN (Print)9783030055318
DOIs
StatePublished - 1 Jan 2019
Event4th International Conference on Technology Trends, CITT 2018 - Babahoyo, Ecuador
Duration: 29 Aug 201831 Aug 2018

Publication series

NameCommunications in Computer and Information Science
Volume895
ISSN (Print)1865-0929

Conference

Conference4th International Conference on Technology Trends, CITT 2018
CountryEcuador
CityBabahoyo
Period29/08/1831/08/18

Keywords

  • Breast cancer
  • Machine learning methods
  • Radiomics
  • ROI classification

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  • Cite this

    Rincón, J. S., Castro-Ospina, A. E., Narváez, F. R., & Díaz, G. M. (2019). Machine learning methods for classifying mammographic regions using the wavelet transform and radiomic texture features. In M. Botto-Tobar, M. D’Armas, M. Zúñiga Sánchez, M. Zúñiga-Prieto, & G. Pizarro (Eds.), Technology Trends - 4th International Conference, CITT 2018, Revised Selected Papers (pp. 617-629). (Communications in Computer and Information Science; Vol. 895). Springer Verlag. https://doi.org/10.1007/978-3-030-05532-5_47