A Novel Method for Detecting Breast Cancer Location Based on Growing GA-FCM Approach

Milad Abaspoor, Saeed Meshgini, Tohid Yousefi Rezaii, Ali Farzamnia

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

Abstract

The main idea of this article is to provide a numerical diagnostic method for breast cancer diagnosis of the MRI images. To achieve this goal, we used the region's growth method to identify the target area. In the area's growth method, based on the similarity or homogeneity of the adjacent pixels, the image is subdivided into distinct areas according to the criteria used for homogeneity analysis to determine their belonging to the corresponding region. In this paper, we used manual methods and use of FCM as the function of genetic algorithm fitness. The presented algorithm is performed for 212 healthy and 110 patients. Results show that GA-FCM method have better performance than hand method to select initial points. The sensitivity of presented method is 0.67. The results of the comparison of the fuzzy fitness function in the genetic algorithm with other technique show that the proposed model is better suited to the Jaccard index with the highest Jaccard values and the lowest Jaccard distance. Among the techniques, the presented works well because of the similarity of techniques and the lowest Jaccard distance. Values close to 0.9 are close to 0.8.

Original languageEnglish
Title of host publication2019 9th International Conference on Computer and Knowledge Engineering, ICCKE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages238-242
Number of pages5
ISBN (Electronic)9781728150758
ISBN (Print)9781728150765
DOIs
Publication statusPublished - 23 Jan 2020
Externally publishedYes
Event9th International Conference on Computer and Knowledge Engineering - Mashhad, Iran, Islamic Republic of
Duration: 24 Oct 201925 Oct 2019
Conference number: 9

Publication series

NameInternational Conference on Computer and Knowledge Engineering, ICCKE
PublisherIEEE
Volume2020
ISSN (Print)2375-1304
ISSN (Electronic)2643-279X

Conference

Conference9th International Conference on Computer and Knowledge Engineering
Abbreviated titleICCKE 2019
Country/TerritoryIran, Islamic Republic of
CityMashhad
Period24/10/1925/10/19

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