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22 May 2020 Mammographic mass identification in dense breasts using multi-scale analysis of structured micro-patterns
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Proceedings Volume 11513, 15th International Workshop on Breast Imaging (IWBI2020); 1151323 (2020) https://doi.org/10.1117/12.2564272
Event: Fifteenth International Workshop on Breast Imaging, 2020, Leuven, Belgium
Abstract
The paper proposes a novel approach for the identification of cancerous regions located in a dense part of a breast. This task is particularly challenging even for experienced radiologists due to lack of clear boundaries between the cancerous and normal tissue. Multi-scale analysis of structured micro-patterns generated from local binary patterns (LBP) was used to generate a very small number of features which allowed for successful detection of cancerous regions. The proposed technique was tested on two publicly available datasets: Digital Database for Screening Mammography (DDSM) and INbreast. The area under the receiver operating characteristic (AUC) curve for DDSM with 2 features only was 0.99 and 0.92 for INbreast with 3 features.
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shelda Sajeev, Mariusz Bajger, Gobert Lee, Chisako Muramatsu, and Hiroshi Fujita "Mammographic mass identification in dense breasts using multi-scale analysis of structured micro-patterns", Proc. SPIE 11513, 15th International Workshop on Breast Imaging (IWBI2020), 1151323 (22 May 2020); https://doi.org/10.1117/12.2564272
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