Utilizing digital breast tomosynthesis projection views correlation for microcalcification enhancement for detection purposes

20 March 2015 Utilizing digital breast tomosynthesis projection views correlation for microcalcification enhancement for detection purposes

Wissam J. Baddar, Eun Joon Kim, Dae Hoe Kim, Yong Man Ro

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Proceedings Volume 9414, Medical Imaging 2015: Computer-Aided Diagnosis; 941421 (2015) https://doi.org/10.1117/12.2082031
Event: SPIE Medical Imaging, 2015, Orlando, Florida, United States

Abstract

This paper presents a novel method for enhancing the contrast of microcalcifications in digital breast tomosynthesis projection views for detection purposes. The proposed method relies on the correlation between the projection views in order to reduce the effect of noise, due to the low-dose exposure, and increase the contrast of the microcalcification particles for microcalcification cluster detection purposes. The method performs a series of multi-shift operations to capture the microcalcification particle movement information and compensate it in order to enhance microcalcification particles contrast. Furthermore, the proposed approach utilizes the projection view correlation in order to reduce the falsely detected regions of interest, and improve the classification of the detected regions into false positives or actual microcalcification clusters. Comparative experiments have been performed to quantitatively measure the contrast enhancement of microcalcification particles and its effect on the MC cluster detection. To that end, the contrast to noise ratio have been calculated and compared with some with previous methods. Furthermore, the free response receiver operating characteristic (FROC) curve have been used to measure the effect of the proposed enhancement on the microcalcification cluster detectability.

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Wissam J. Baddar, Eun Joon Kim, Dae Hoe Kim, and Yong Man Ro "Utilizing digital breast tomosynthesis projection views correlation for microcalcification enhancement for detection purposes", Proc. SPIE 9414, Medical Imaging 2015: Computer-Aided Diagnosis, 941421 (20 March 2015); https://doi.org/10.1117/12.2082031

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KEYWORDS

Photovoltaics

Particles

Digital breast tomosynthesis

Breast

Feature extraction

Signal to noise ratio

Gaussian filters

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