Structured Micro-Pattern Based LBP Features for Classification of Masses in Dense Breasts

Shelda Sajeev, Mariusz Bajger, Gobert Lee

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

2 Citations (Scopus)

Abstract

Cancerous masses detection in dense background is a particularly challenging task for even experienced radiologists due to their similarity of intensity with the overlapped normal dense tissues, obscured boundaries and low contrast between mass and surrounding regions. This paper proposes a novel approach for the identification of cancerous regions located in a dense part of a breast. Careful analysis of nine structured micro-patterns generated using LBP technique revealed the most prominent ones, allowing for successful classification of cancerous regions. The proposed approach was evaluated using two mammographic databases: the publicly available Digital Database for Screening Mammography (DDSM), and a local database of mammograms. A total of 535 Regions of Interest (ROIs) were used (301 ROIs extracted from DDSM and 234 from local database). All 535 ROIs were localized in dense backgrounds of breasts. The experiments showed that features generated from structured micro-patterns can produce very effective and efficient texture descriptors of cancerous ROIs. With only 4 features we obtained an AUC score of 0.957 for DDSM and 0.891 for local dataset using Fischer Linear Discriminant Analysis (LDA) classifier.

Original languageEnglish
Title of host publicationDICTA 2017 - 2017 International Conference on Digital Image Computing
Subtitle of host publicationTechniques and Applications
EditorsYi Guo, Manzur Murshed, Zhiyong Wang, David Dagan Feng, Hongdong Li, Weidong Tom Cai, Junbin Gao
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-8
Number of pages8
ISBN (Electronic)9781538628393
DOIs
Publication statusPublished - 19 Dec 2017
Externally publishedYes
Event2017 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2017 - Sydney, Australia
Duration: 29 Nov 20171 Dec 2017

Publication series

NameDICTA 2017 - 2017 International Conference on Digital Image Computing: Techniques and Applications
Volume2017-December

Conference

Conference2017 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2017
CountryAustralia
CitySydney
Period29/11/171/12/17

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    Sajeev, S., Bajger, M., & Lee, G. (2017). Structured Micro-Pattern Based LBP Features for Classification of Masses in Dense Breasts. In Y. Guo, M. Murshed, Z. Wang, D. D. Feng, H. Li, W. T. Cai, & J. Gao (Eds.), DICTA 2017 - 2017 International Conference on Digital Image Computing: Techniques and Applications (pp. 1-8). (DICTA 2017 - 2017 International Conference on Digital Image Computing: Techniques and Applications; Vol. 2017-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DICTA.2017.8227493