Imaging of Fiber-Like Structures in Digital Breast Tomosynthesis
Sean D. Rose, Emil Y. Sidky, Ingrid Reiser, Xiaochuan Pan

TL;DR
This paper investigates how different image reconstruction algorithms and regularization parameters affect the visibility of fiber-like structures in digital breast tomosynthesis, using simulations, phantom data, and clinical cases.
Contribution
It introduces a quantitative metric to assess orientation dependence of fiber signals and analyzes the impact of regularization on their conspicuity in DBT imaging.
Findings
Orientation significantly affects fiber visibility at low regularization.
Higher regularization reduces orientation dependence but increases depth blur.
Simulation results align with physical phantom and clinical data.
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. This 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,…
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