Unberath M (2017)
Publication Language: English
Publication Type: Thesis
Publication year: 2017
Pages Range: 130
URI: https://opus4.kobv.de/opus4-fau/frontdoor/index/index/docId/8553
Rotational angiography using C-arm scanners enables intra-operative 3-D imaging
that has proved beneficial for diagnostic assessment and interventional guidance. Despite
previous efforts, rotational angiography was not yet successfully established in
clinical practice for coronary artery imaging but remains subject of intensive academic
research. 3-D reconstruction of the coronary vasculature is impeded by severe lateral
truncation of the thorax, as well as substantial intra-scan respiratory and cardiac motion.
Reliable and fully automated solutions to all of the aforementioned problems
are required to pave the way for clinical application of rotational angiography and,
hence, sustainably change the state-of-care.
Within this thesis, we identify shortcomings of existing approaches and devise algorithms
that effectively address non-recurrent object motion, severe angular undersampling,
and the dependency on projection domain segmentations. The proposed
methods build upon virtual digital subtraction angiography (vDSA) that voids image
truncation and enables prior-reconstruction-free respiratory motion compensation using
both Epipolar consistency conditions (ECC) and auto-focus measures (AFMs).
The motion-corrected geometry is then used in conjunction with a novel 4-D iterative
algorithm that reconstructs images at multiple cardiac phases simultaneously. The
method allows for communication among 3-D volumes by regularizing the temporal
total variation (tTV) and thus implicitly addresses the problem of insufficient data
very effectively. Finally, we consider symbolic coronary artery reconstruction from
very few observations and develop generic extensions that consist of symmetrization,
outlier removal, and projection domain-informed topology recovery. When applied to
two state-of-the-art reconstruction algorithms, the proposed methods substantially
reduce problems due to incorrect 2-D centerlines, promoting improved performance.
Given that all methods proved effective on the same in silico and in vivo data sets,
we are confident that the proposed algorithms bring rotational coronary angiography
one step closer to clinical applicability.
APA:
Unberath, M. (2017). Signal Processing for Interventional X-ray-based Coronary Angiography (Dissertation).
MLA:
Unberath, Mathias. Signal Processing for Interventional X-ray-based Coronary Angiography. Dissertation, 2017.
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