Semi-automated segmentation and classification of digital breast tomosynthesis reconstructed images.
Semi-automated segmentation and classification of digital breast tomosynthesis reconstructed images.
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DOI：
10.1109/iembs.2011.6091528
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发表时间：
2011
期刊：
影响因子：
--
通讯作者：
Paulsen KD
中科院分区：
文献类型：
--
作者：
Vedantham S;Shi L;Karellas A;Michaelsen KE;Krishnaswamy V;Pogue BW;Paulsen KD
Digital breast tomosynthesis (DBT) is a limited-angle tomographic x-ray imaging technique that reduces the effect of tissue super position observed in planar mammography. An integrated imaging platform that combines DBT with near infrared spectroscopy (NIRS) to provide co-registered anatomical and functional imaging is under development. Incorporation of anatomic priors can benefit NIRS reconstruction. In this work, we provide a segmentation and classification method to extract potential lesions, as well as adipose, fibroglandular, muscle and skin tissue in reconstructed DBT images that serve as anatomic priors during NIRS reconstruction. The method may also be adaptable for estimating tumor volume, breast glandular content, and for extracting lesion features for potential application to computer aided detection and diagnosis.
