Microcalcification detection in mammography image using computer-aided detection based on convolutional neural network-Reference-Cited by-同舟云学术

Microcalcification detection in mammography image using computer-aided detection based on convolutional neural network

Published:2021 Issue: Volume: Page:
ISSN:0094-243X
Container-title:PROCEEDINGS OF THE INTERNATIONAL CONFERENCE AND SCHOOL ON PHYSICS IN MEDICINE AND BIOSYSTEM (ICSPMB): Physics Contribution in Medicine and Biomedical Applications
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Author:

Hakim A. N. R.,Prajitno P.,Soejoko D. S.

Publisher

AIP Publishing

Link

http://aip.scitation.org/doi/pdf/10.1063/5.0047828

Reference20 articles.

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2. P. C. Stomper, J. Geradts, S. B. Edge, E. G. Levine. Mammographic predictors of the presence and size of invasive carcinomas associated with malignant microcalcification lesions without a mass. American Journal of Roentgenology. 2003.

3. M. R. Del Turco, P. Mantellini, S. Ciatto, et al. Full-field digital versus screen-film mammography: comparative accuracy in concurrent screening cohorts. American Journal of Roentgenology. 2007.

4. M. Heath, K. Bowyer, D. Kopans, R. Moore, P. Kegelmeyer. The digital database for screening mammography. In: Proceedings of the 5th International Workshop on Digital Mammography. Medical Physics Publishing (Madison,WI), pp.662–671, 2000.

5. C. J. Vyborny and R. A. Schmidt. Technical image quality and the visibility of mammographic detail, in Syllabus: A Categorical Course in Physics-Technical Aspects of Breast Imaging, A. G. Haus and M. J. Yaffe, Eds. Oak Book III: Radiological Society of North America, pp.103–111, 1994.

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