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Figure 1. Biplane cine-angiographic x-ray equipment used in the catheter lab to acquire images for quantitative
leftventricleanalysis.
The gold standard for quantitative left ventricle analysis in the catheter lab is based on the evaluation
of end-diastolic (ED) and end-systolic (ES) endocardial contour information gathered from these 2-
D projection images. The ED and the ES volume are calculated (by applying e.g. the Area-Length
method) and used to determine ejection fraction (EF), i.e. the volume that is squeezed out during
contraction. Contour information is further utilized by wall motion analysis methods (like e.g. the
Centerline method) to quantify myocardial viability. However, since 3-D information is lost due to
projection, volumetric diagnostic parameters, like EF, can only be approximated and wall motion
is only evaluable for LV surface areas with the boundary visible in the projection image. Novel
approachesaimat reconstructing thespatio-temporalshapeof theLVtoperformanalysis in3-D[10].
2. RelatedWork
Inclassical computed tomography(CT),hundredsofprojectionsareacquiredbya fast rotatingx-ray
gantry. Analytical and algebraic reconstruction techniques exploit this dense information to yield
voxel values that vary within a continuous range. However, these techniques typically fail if merely
two (noisy) projections are available. C-arm CT is a relatively young and hybrid type of imaging
modality, where the C-arm is rotated during acquisition to increase the number of projections. Tech-
niquesknownfromCTcan thenbeutilized toaddress the reconstructionproblem[8]. In thecatheter
lab, however, the application of C-arm CT is challenged by the higher amount of x-ray dose and
bolus compared with conventional x-ray angiography (XA), and the slower rotational speed of the
C-arm compared with classical CT when imaging the rapidly moving heart. Whether C-arm CT will
substituteXAas a routinemethod in future remains to beseen [9].
Unlike classical (continuous) CT, discrete tomography focuses on reconstruction problems where
only a small number of projections – as small as two – are available and the object’s intensity levels
are limited, i.e. discrete, and known a-priori [3]. Using additional a-priori information is crucial
whentrying tosolvesuchunder-determinedandambiguousproblems, since thiscanreduce thespace
of possible solutions and improve the ability to deal with noisy projection data. Some of the early
approaches published in the field of 3-D LV shape recovery from XA rely on the assumption that
ventricular cross-sections follow certain geometric priors (like connectedness, convexity, symmetry,
roundness,etc.),however, this isusually toorestrictiveinpractice. IntheworkofPrauseandOnnasch
[7], digitized post-mortem human LV casts are used as a-priori information. Other approaches often
donot incorporateanatomical a-priori information at all [5], [6].
46
Proceedings
OAGM & ARW Joint Workshop 2016 on "Computer Vision and Robotics“
- Title
- Proceedings
- Subtitle
- OAGM & ARW Joint Workshop 2016 on "Computer Vision and Robotics“
- Authors
- Peter M. Roth
- Kurt Niel
- Publisher
- Verlag der Technischen Universität Graz
- Location
- Wels
- Date
- 2017
- Language
- English
- License
- CC BY 4.0
- ISBN
- 978-3-85125-527-0
- Size
- 21.0 x 29.7 cm
- Pages
- 248
- Keywords
- Tagungsband
- Categories
- International
- Tagungsbände