@inproceedings{3eae4e7593c441d2a74f49824f1f59a5,
title = "Conventional mammographic image generation method with increased calcification sensitivity based on dual-energy",
abstract = "The visualization of calcifications could be obscured in mammograms because of overlapping of tissue structures. Dual-energy digital mammography (DEDM) can generate tissue-subtracted image for improving the detectability of breast calcifications, but the mass information is missing. This paper proposes a conventional mammographic image generation method with increased calcification sensitivity based on DEDM. Firstly, a conventional mammographic image is generated with low-energy and high-energy images based on multi-scale decomposition and reconstruction. Secondly, the tissue-subtracted {"}calcification image{"} is generated using a nonlinear inverse mapping function with calcification pixels marked. Finally, the density values of the marked calcification pixels in the reconstructed mammographic image are increased for better visualization. Preliminary results show that the proposed DEDM method can generate both calcification and conventional mammogram-like images and the calcification sensitivity is increased. The CNR of calcifications of 50\% glandular ratio has been increased from 2.75 to 9.32.",
keywords = "calcification sensitivity, digital mammography, dual-energy, multi-scale",
author = "Xi Chen and Xuanqin Mou",
year = "2014",
doi = "10.1007/978-3-319-07887-8\_64",
language = "英语",
isbn = "9783319078861",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "460--467",
booktitle = "Breast Imaging - 12th International Workshop, IWDM 2014, Proceedings",
note = "12th International Workshop on Breast Imaging, IWDM 2014 ; Conference date: 29-06-2014 Through 02-07-2014",
}