Matching Tumour Candidate Points in Multiple Mammographic Views for Breast Cancer Detection

Mohamed Abdel-Nasser, Antonio Moreno, Mohamed A. Abdelwahab, Adel Saleh, Saddam Abdulwahab, Vivek K. Singh, Domenec Puig

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

4 Citations (Scopus)

Abstract

Matching candidate points from multiple mammographic views corresponding to the same patient may lead to an improvement in the accuracy of Computer Aided Diagnosis systems and it can help the radiologists to detect breast cancer in early stages, leading to a reduction of the percentage of mortality. In this paper, we propose a matching approach in order to detect correspondences between some candidate points from multiple mammographic views. Initially, a Scale Invariant Feature Transform detector is used to determine some candidate points in the mammographic views, then a combination between texture features is proposed to check the abnormality of the local region that surrounds each candidate point. The candidate points can be matched by integrating the information given by the texture analysis, the distance from the nipple and the location of the candidate points relative to the nipple. Some experiments are presented to show the effectiveness of the proposed approach.

Original languageEnglish
Title of host publicationProceedings of 2019 International Conference on Innovative Trends in Computer Engineering, ITCE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages202-207
Number of pages6
ISBN (Electronic)9781538652602
DOIs
Publication statusPublished - Feb 20 2019
Externally publishedYes
Event2019 International Conference on Innovative Trends in Computer Engineering, ITCE 2019 - Aswan, Egypt
Duration: Feb 2 2019Feb 4 2019

Publication series

NameProceedings of 2019 International Conference on Innovative Trends in Computer Engineering, ITCE 2019

Conference

Conference2019 International Conference on Innovative Trends in Computer Engineering, ITCE 2019
CountryEgypt
CityAswan
Period2/2/192/4/19

All Science Journal Classification (ASJC) codes

  • Safety, Risk, Reliability and Quality
  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Signal Processing
  • Information Systems and Management

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