IEEE Access (Jan 2023)

A New Fat-Removal-Based Preprocessing Pipeline for MLO View in Digital Mammograms

  • Juanita Hernandez Lopez,
  • Juan Humberto Sossa Azuela,
  • Alberto Salvador Nunez Varela,
  • Cesar Augusto Ramirez Gamez,
  • Virginia Canseco Gonzalez,
  • Francisco Eduardo Martinez Perez,
  • Sandra Edith Nava Munoz,
  • Hector Gerardo Perez Gonzalez,
  • Jose Ignacio Nunez Varela

DOI
https://doi.org/10.1109/ACCESS.2023.3236612
Journal volume & issue
Vol. 11
pp. 6078 – 6091

Abstract

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Specific anatomical structures from the female body, such as the axillary slope, armpit, pectoral muscle, or abdominal tissue, can be present in mammograms and might affect the proper mammogram analysis, especially in female populations with overweight issues, as is the case in Mexico. This work aims to determine if better results can be obtained in an automatic mammogram analysis by removing the abdominal and axillary fatty tissues as a preprocessing step. The experimentation is carried out by applying a pectoral muscle segmentation technique in a Mexican mammogram dataset and comparing the results by removing the fatty tissues from the same mammograms. Furthermore, the same experimentation is performed using the Portuguese public datasets, INbreast and BCDR. The conducted experiment will allow us to determine the differences in results across different populations. The fat removal method is based on the breast contour-edge from which points of interest are detected to cut the fat tissue. Our results suggest that the proposed method is suitable as a preprocessing technique, obtaining a 94.18% of acceptance, according to the qualitative analysis performed, and showed that removing the fatty tissue yields better results if the mammogram contains significant fatty tissue such as in the mammograms of Mexican patients.

Keywords