Comparison of two-dimensional synthesized mammograms versus original digital mammograms: A quantitative assessment

Document Type

Article

Publication Date

2-1-2021

Abstract

This study objectively evaluates the similarity between standard full-field digital mammograms and two-dimensional synthesized digital mammograms (2DSM) in a cohort of women undergoing mammography. Under an institutional review board-approved data collection protocol, we retrospectively analyzed 407 women with digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM) examinations performed from September 1, 2014, through February 29, 2016. Both FFDM and 2DSM images were used for the analysis, and 3216 available craniocaudal (CC) and mediolateral oblique (MLO) view mammograms altogether were included in the dataset. We analyzed the mammograms using a fully automated algorithm that computes 152 structural similarity, texture, and mammographic density-based features. We trained and developed two different global mammographic image feature analysis-based breast cancer detection schemes for 2DSM and FFDM images, respectively. The highest structural similarity features were obtained on the coarse Weber Local Descriptor differential excitation texture feature component computed on the CC view images (0.8770) and MLO view images (0.8889). Although the coarse structures are similar, the global mammographic image feature-based cancer detection scheme trained on 2DSM images outperformed the corresponding scheme trained on FFDM images, with area under a receiver operating characteristic curve (AUC) = 0.878 +/- 0.034 and 0.756 +/- 0.052, respectively. Consequently, further investigation is required to examine whether DBT can replace FFDM as a standalone technique, especially for the development of automated objective-based methods.

Keywords

Mammography, Algorithms, Breast density, Two-dimensional synthesized mammograms, Structural similarity

Divisions

fac_med

Funders

Electrical and Computer Systems Engineering, School of Engineering, Monash University Malaysia,Advanced Engineering Platform, School of Engineering, Monash University Malaysia,University of Malaya Research Grant (PO035-2015)

Publication Title

Medical & Biological Engineering & Computing

Volume

59

Issue

2

Publisher

Springer Heidelberg

Publisher Location

TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY

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