Quantitative Digital Tomosynthesis Mammography for Improved Breast Cancer Detection and Diagnosis

Abstract : The goal of the project is to develop advanced Digital Tomosynthesis Mammography (DTM) reconstruction algorithms with artifact reduction methods to optimize image quality and minimize image artifacts, and to improve quantitative linear attenuation coefficient estimation of breast tissues. When fully developed, the DTM can provide radiologists improved quantitative, three-dimensional volumetric information of the breast tissue, and assist in breast cancer detection and diagnosis. During this project year, we have performed the following tasks: (1) implementation and comparison of multiple algorithms for limited-angle cone-beam tomography in DTM reconstruction, and development of dedicated breast phantom and image quality evaluation measures, (2) development of efficient algorithm for iterative DTM reconstruction method by utilization of breast shape information, (3) development of artifact reduction methods to remove image artifacts from multiple sources, and (4) investigation of the impact of DTM system and imaging condition parameters on the reconstructed image quality. In summary, we have completed a number of studies in the development of advanced reconstruction algorithms for DTM. We have made progress in two tasks proposed in the project. We have found that our advanced reconstruction algorithms can provide improved reconstructed DTM image quality with minimized artifacts. We will continue the development of scatter correction and beam hardening correction methods in DTM reconstruction algorithms to improve the quantitative estimation of the linear attenuation properties of breast tissue in the coming years.

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