11 January 2019 Imaging of fiber-like structures in digital breast tomosynthesis
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Abstract
Fiber-like features are an important aspect of breast imaging. Vessels and ducts are present in all breast images, and spiculations radiating from a mass can indicate malignancy. Accordingly, fiber objects are one of the three types of signals used in the American College of Radiology digital mammography (ACR-DM) accreditation phantom. Our work focuses on the image properties of fiber-like structures in digital breast tomosynthesis (DBT) and how image reconstruction can affect their appearance. The impact of DBT image reconstruction algorithm and regularization strength on the conspicuity of fiber-like signals of various orientations is investigated in simulation. A metric is developed to characterize this orientation dependence and allow for quantitative comparison of algorithms and associated parameters in the context of imaging fiber signals. The imaging properties of fibers, characterized in simulation, are then demonstrated in detail with physical DBT data of the ACR-DM phantom. The characterization of imaging of fiber signals is used to explain features of an actual clinical DBT case. For the algorithms investigated, at low regularization setting, the results show a striking variation in conspicuity as a function of orientation in the viewing plane. In particular, the conspicuity of fibers nearly aligned with the plane of the x-ray source trajectory is decreased relative to more obliquely oriented fibers. Increasing regularization strength mitigates this orientation dependence at the cost of increasing depth blur of these structures.
© 2019 Society of Photo-Optical Instrumentation Engineers (SPIE) 2329-4302/2019/$25.00 © 2019 SPIE
Sean D. Rose, Emil Y. Sidky, Ingrid Reiser, and Xiaochuan Pan "Imaging of fiber-like structures in digital breast tomosynthesis," Journal of Medical Imaging 6(3), 031404 (11 January 2019). https://doi.org/10.1117/1.JMI.6.3.031404
Received: 27 April 2018; Accepted: 10 December 2018; Published: 11 January 2019
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CITATIONS
Cited by 6 scholarly publications.
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KEYWORDS
Digital breast tomosynthesis

Reconstruction algorithms

Structured optical fibers

Image restoration

Sensors

Image filtering

Data modeling

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