Paper
16 March 2020 Quantitative evaluation of virtual monochromatic imaging for detection of microcalcifications
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Abstract
The detection of microcalcification on mammograms is known as the most important feature. Microcalcifications are difficult to distinguish because they have low contrast in mammography due to size and breast density. The purpose of this study was to evaluate the feasibility of virtual monochromatic image (VMI) for quantitative assessment of the appropriate energy region for detection of malignant microcalcifications. The photon-counting spectral mammography system was modeled using Geant4 Application for Tomographic Emission (GATE) simulation tools. The breast phantom used a 50/50 ratio of adipose/glandular tissue and microcalcifications used calcium hydroxyapatite (Ca5(PO4)3(OH)), which is mainly malignant. Microcalcifications with various sizes ranging from 150 μm to 550 μm were embedded into the breast phantom. In this study, projection based VMI was used. This study quantitatively evaluates the appropriate energy region in terms of image quality using VMI technique. The results showed that VM images were optimized at an energy range of approximately 26 to 27 keV. In order to verify the usefulness of the results obtained from the VM images, the CNR was evaluated according to the microcalcification size using the bin images obtained by setting various energy thresholds based on the photon-counting detector. Compared to the results of VM images, the results of bin images showed a similar tendency. In this study, we investigated the optimum energy of monochromatic images for breast diagnostic applications. By setting the optimal energy range using VMI, we can identify microcalcifications better in mammography and expect to reduce the frequency of additional examination.
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Hyemi Kim, Minjae Lee, Dohyeon Kim, and Hee-Joung Kim "Quantitative evaluation of virtual monochromatic imaging for detection of microcalcifications", Proc. SPIE 11312, Medical Imaging 2020: Physics of Medical Imaging, 113125A (16 March 2020); https://doi.org/10.1117/12.2549191
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KEYWORDS
Breast

Mammography

Tissues

Image quality

X-rays

Sensors

Calcium

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