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- Bakic, Predrag R., et al.
(författare)
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Pre-processing for image quality improvement in simultaneous DBT and mechanical imaging
- 2020
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Ingår i: Medical Imaging 2020 : Physics of Medical Imaging - Physics of Medical Imaging. - : SPIE. - 1605-7422. - 9781510633919 ; 11312
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Konferensbidrag (refereegranskat)abstract
- Simultaneous digital breast tomosynthesis (DBT) and mechanical imaging (MI) offer the potential to combine anatomic information from DBT with functional information from MI. This makes it possible to associate tissue stiffness with specific anatomic structures in the breast, a combination that can reduce false-positive findings by using the MI data to discriminate between ambiguous lesions in DBT. This, in turn, will reduce the frequency of negative biopsies. Simultaneous imaging requires that the MI sensor array be present during DBT acquisition. This introduces artifacts, since the sensor is attenuating. Previously, we demonstrated that the DBT reconstruction could be modified to reduce sensor conspicuity in DBT images. In this paper, we characterize the relative attenuation of the breast and the sensor, to calculate the artifact reduction in DBT reconstruction. We concentrate on pre-processing DBT projections prior to reconstruction. Using commercially available a DBT system, we have confirmed that the sensor array does not completely attenuate the x-rays. This suggests that a pre-processing method based upon flat fielding can be used to reduce artifacts. In a proof-of-concept study, we performed flat fielding by combining DBT projections of the MI sensor with and without an anthropomorphic breast phantom. Visual evaluation confirmed substantially improved image quality. The artifacts were reduced throughout the image for all sensor elements. Few residual artifacts are noticeable where the phantom thickness decreases. The investigation of additional pre-processing, including beam hardening correction is ongoing. Future work includes quantitative validation, noise stabilization, and method optimization in virtual clinical trials and subsequent patient studies.
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