9 March 2018 Analysis of volume overestimation artifacts in the breast outline segmentation in tomosynthesis
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Abstract
In digital breast tomosynthesis (DBT), the reconstruction is calculated from x-ray projection images acquired over a small range of angles. One step in the reconstruction process is to identify the pixels that fall outside the shadow of the breast, to segment the breast from the background (air). In each projection, rays are back-projected from these pixels to the focal spot. All voxels along these rays are identified as air. By combining these results over all projections, a breast outline can be determined for the reconstruction. This paper quantifies the accuracy of this breast segmentation strategy in DBT. In this study, a physical phantom modeling a breast under compression was analyzed with a prototype next-generation tomosynthesis (NGT) system described in previous work. Multiple wires were wrapped around the phantom. Since the wires are thin and high contrast, their exact location can be determined from the reconstruction. Breast parenchyma was portrayed outside the outline defined by the wires. Specifically, the size of the phantom was overestimated along the posteroanterior (PA) direction; i.e., perpendicular to the plane of conventional source motion. To analyze how the acquisition geometry affects the accuracy of the breast outline segmentation, a computational phantom was also simulated. The simulation identified two ways to improve the segmentation accuracy; either by increasing the angular range of source motion laterally or by increasing the range in the PA direction. The latter approach is a unique feature of the NGT design; the advantage of this approach was validated with our prototype system.
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Raymond J. Acciavatti, Alejandro Rodríguez-Ruiz, Trevor L. Vent, Predrag R. Bakic, Ingrid Reiser, Ioannis Sechopoulos, Andrew D. A. Maidment, "Analysis of volume overestimation artifacts in the breast outline segmentation in tomosynthesis", Proc. SPIE 10573, Medical Imaging 2018: Physics of Medical Imaging, 1057359 (9 March 2018); doi: 10.1117/12.2293253; https://doi.org/10.1117/12.2293253
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