Multilevel segmentation for automatic detection of malignant masses in digital mammograms based on threshold comparison

Erick Rodriguez-Esparza, Laura A. Zanella-Calzada, DIego Oliva, Salvador Hinojosa, Marco Perez-Cisneros

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

1 Citation (Scopus)

Abstract

Digital image processing implies a fundamental process in the field of medicine, since it supports the improvement of images facilitating their interpretation for the specialists. A technique that has had great relevance is image segmentation, applied to mammography images, in order to improve the diagnosis of breast cancer disease. In this work it is proposed the implementation of a new multilevel segmentation approach based on the minimum cross-entropy threshold - Harris Hawks Optimization (MCET-HHO) metaheuristic algorithm, where five different levels are used in order to compare the behavior of the thresholds applied in mammograms with presence of cancer by allowing the identification of malignant tumors. According to the results, by including four levels in the segmentation of the image, it is possible to identify with a significantly high precision the region of interest (ROI) where the tumor is located, obtaining a similarity of 0.902 with the ROI identified by the specialist. Therefore, it is concluded that the implementation of the MCET-HHO algorithm for multilevel segmentation of mammograms allows to determine the ROI that contains malignant masses, presenting a preliminary support tool for the diagnosis of breast cancer.

Original languageEnglish
Title of host publication2019 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728156668
DOIs
Publication statusPublished - Nov 2019
Externally publishedYes
Event6th IEEE Latin American Conference on Computational Intelligence, LA-CCI 2019 - Guayaquil, Ecuador
Duration: 11 Nov 201915 Nov 2019

Publication series

Name2019 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2019

Conference

Conference6th IEEE Latin American Conference on Computational Intelligence, LA-CCI 2019
CountryEcuador
CityGuayaquil
Period11.11.1915.11.19

Keywords

  • Digital Image Processing
  • Mammograms
  • MCET-HHO algorithm
  • Metaheuristic Algorithm
  • Multilevel Segmentation

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction

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    Rodriguez-Esparza, E., Zanella-Calzada, L. A., Oliva, DI., Hinojosa, S., & Perez-Cisneros, M. (2019). Multilevel segmentation for automatic detection of malignant masses in digital mammograms based on threshold comparison. In 2019 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2019 [9037030] (2019 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/LA-CCI47412.2019.9037030