Poster + Paper
7 April 2023 Anatomy registration via patient sensing for chest x-ray digital tomosynthesis
Yang Zhao, Alex Chen, Eric Tkaczyk, Jie Liu
Author Affiliations +
Conference Poster
Abstract
Chest X-ray is one of the most commonly performed radiologic procedures for respiratory diseases. Digital tomosynthesis (DTS) provides volumetric anatomic information at lower cost and dose compared to computed tomography (CT). However, current DTS system provides insufficient patient positioning feedback and requires a large number of reconstructed slices in order to ensure imaging the entirety of targeted anatomy. We propose an anatomy registration prototype using measurements from RGB-D cameras to 1) assist acquisition workflow, 2) provide individual-specific anatomical information to improve tomosynthesis reconstruction. Our experiments show that anatomy registration can provide real-time feedback of patient 2D position and body thickness. Our reconstruction simulations show that the anatomy and body information can speed up DTS reconstruction, reduce the number of redundant tomosynthesis slices, and help reduce image interpretation time.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yang Zhao, Alex Chen, Eric Tkaczyk, and Jie Liu "Anatomy registration via patient sensing for chest x-ray digital tomosynthesis", Proc. SPIE 12463, Medical Imaging 2023: Physics of Medical Imaging, 1246335 (7 April 2023); https://doi.org/10.1117/12.2654160
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KEYWORDS
Anatomy

Reconstruction algorithms

Lung

Chest

Cameras

Image registration

Chest imaging

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