Delimitation of Benign and Malignant Masses in Breast Ultrasound by Clustering of Intuitionistic Fuzzy Superpixels Using DBSCAN Algorithm

Dante Mújica-Vargas, Antonio Luna-Álvarez, Alberto Rosales-Silva, Andrea Palacios-Cervantes

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this study, we propose a scheme to delimit benign and malignant masses in breast ultrasound images. It consists of two stages: superpixels extraction by an Intuitionistic Fuzzy algorithm, which considers the local information of the image to develop a local segmentation; and clustering the superpixels by means of DBSCAN algorithm. The proposal does not require preprocessing of noise reduction inherent to this type of medical images or enhancement of features. The effectiveness of our proposal is verified by quantitative and qualitative results.

Original languageEnglish
Title of host publicationPattern Recognition - 14th Mexican Conference, MCPR 2022, Proceedings
EditorsOsslan Osiris Vergara-Villegas, Vianey Guadalupe Cruz-Sánchez, Juan Humberto Sossa-Azuela, Jesús Ariel Carrasco-Ochoa, José Francisco Martínez-Trinidad, José Arturo Olvera-López
PublisherSpringer Science and Business Media Deutschland GmbH
Pages348-359
Number of pages12
ISBN (Print)9783031077494
DOIs
StatePublished - 2022
Event14th Mexican Conference on Pattern Recognition, MCPR 2022 - Ciudad Juárez, Mexico
Duration: 22 Jun 202225 Jun 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13264 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th Mexican Conference on Pattern Recognition, MCPR 2022
Country/TerritoryMexico
CityCiudad Juárez
Period22/06/2225/06/22

Keywords

  • DBSCAN
  • Intuitionistic fuzzy clustering
  • Ultrasound image delimitation

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