ArticleInternational journal of cardiac imaging2000
A system for determination of 3D vessel tree centerlines from biplane images.
Article in International journal of cardiac imaging, 2000. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- A multi-stage neural network approach for coronary 3D reconstruction from uncalibrated X-ray angiography images.Scientific reports · 2023Article
- Three-Dimensional Analysis of the In Vivo Motion of Implantable Cardioverter Defibrillator Leads.Cardiovascular engineering and technology · 2022Article
- The importance of three dimensional coronary artery reconstruction accuracy when computing virtual fractional flow reserve from invasive angiography.Scientific reports · 2021Article
- Article
- Assessment of obstruction length and optimal viewing angle from biplane X-ray angiograms.The international journal of cardiovascular imaging · 2010Article
- Clinical evaluation of angiographic multiple-view 3D reconstruction.International journal of computer assisted radiology and surgery · 2009Article
- Effects of point configuration on the accuracy in 3D reconstruction from biplane images.Medical physics · 2005Article
- Efficient Algorithms for Determining 3-D Bi-Plane Imaging Geometry.Journal of combinatorial optimization · 2005Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
With the increasing number and complexity of therapeutic coronary interventions, there is an increasing need for accurate quantitative measurements. These interventions and measurements may be facilitated by accurate and reproducible magnifications and orientations of the vessel structures, specifically by accurate 3D vascular tree centerlines. A number of methods have been proposed to calculate 3D vascular tree centerlines from biplane images. In general, the calculated magnifications and orientations are accurate to within approximately 1-3% and 2-5 degrees, respectively. Here, we present a complete system for determination of the 3D vessel centerlines from biplane angiograms without the use of a calibration object. Subsequent to indication of the vessel centerlines, the imaging geometry and 3D centerlines are calculated automatically and within approximately 2 min. The system was evaluated in terms of the intra- and inter-user variations of the various calculated quantities. The reproducibilities obtained with this system are comparable to or better than the accuracies and reproducibilities quoted for other proposed methods. Based on these results and those reported in earlier studies, we believe that this system will provide accurate and reproducible vascular tree centerlines from biplane images while the patient is still on the table, and thereby will facilitate interventions and associated quantitative analyses of the vasculature.
Indexed as
Identifiers
11215917What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.