Evidence map›Paper›PMID 30977093›Full record

ArticleInternational journal of computer assisted radiology and surgery2019

Preliminary results of DSA denoising based on a weighted low-rank approach using an advanced neurovascular replication system.

Sai Gokul Hariharan, Christian Kaethner, Norbert Strobel, Markus Kowarschik, Julie DiNitto, Shadi Albarqouni, Rebecca Fahrig, Nassir Navab

Abstract read
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In one paragraph

Article in International journal of computer assisted radiology and surgery, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 36% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. Application of deblur technology for improving the clarity of digital subtractive angiography.Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 7 institutions in 2 countries.

Sai Gokul HariharanComputer Aided Medical Procedures, Technische Universität München, Munich, Germany. saigokul.hariharan@tum.de.ORCID http://orcid.org/0000-0002-4446-6799
Christian KaethnerSiemens Healthineers AG, Advanced Therapies, Forchheim, Germany.
Norbert StrobelSiemens Healthineers AG, Advanced Therapies, Forchheim, Germany.
Markus KowarschikComputer Aided Medical Procedures, Technische Universität München, Munich, Germany.
Julie DiNittoSiemens Medical Solutions, Hoffman Estates, USA.
Shadi AlbarqouniComputer Aided Medical Procedures, Technische Universität München, Munich, Germany.
Rebecca FahrigSiemens Healthineers AG, Advanced Therapies, Forchheim, Germany.
Nassir NavabComputer Aided Medical Procedures, Technische Universität München, Munich, Germany.
Siemens Healthineers (Germany) · DEFriedrich-Alexander-Universität Erlangen-Nürnberg · DEJohns Hopkins University · USSiemens (Germany) · DESiemens (United States) · USTechnical University of Applied Sciences Würzburg-Schweinfurt · DETechnical University of Munich · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose2D digital subtraction angiography (DSA) has become an important technique for interventional neuroradiology tasks, such as detection and subsequent treatment of aneurysms. In order to provide high-quality DSA images, usually undiluted contrast agent and a high X-ray dose are used. The iodinated contrast agent puts a burden on the patients' kidneys while the use of high-dose X-rays expose both patients and medical staff to a considerable amount of radiation. Unfortunately, reducing either the X-ray dose or the contrast agent concentration usually results in a sacrifice of image quality. MATERIALS AND

methodsTo denoise a frame, the proposed spatiotemporal denoising method utilizes the low-rank nature of a spatially aligned temporal sequence where variation is introduced by the flow of contrast agent through a vessel tree of interest. That is, a constrained weighted rank-1 approximation of the stack comprising the frame to be denoised and its temporal neighbors is computed where the weights are used to prevent the contribution of non-similar pixels toward the low-rank approximation. The method has been evaluated using a vascular flow phantom emulating cranial arteries into which contrast agent can be manually injected (Vascular Simulations Replicator, Vascular Simulations, Stony Brook NY, USA). For the evaluation, image sequences acquired at different dose levels as well as different contrast agent concentrations have been used.

resultsQualitative and quantitative analyses have shown that with the proposed approach, the dose and the concentration of the contrast agent could both be reduced by about 75%, while maintaining the required image quality. Most importantly, it has been observed that the DSA images obtained using the proposed method have the closest resemblance to typical DSA images, i.e., they preserve the typical image characteristics best.

conclusionUsing the proposed denoising approach, it is possible to improve the image quality of low-dose DSA images. This improvement could enable both a reduction in contrast agent and radiation dose when acquiring DSA images, thereby benefiting patients as well as clinicians. Since the resulting images are free from artifacts and as the inherent characteristics of the images are also preserved, the proposed method seems to be well suited for clinical images as well.

Indexed as

Phantoms, ImagingAngiography, Digital SubtractionArteriesArtifactsContrast MediaHumansImage Processing, Computer-AssistedContrast MediaDigital subtraction angiographyLow-dose X-ray sequencesSpatiotemporal denoisingWeighted low-rank approximation

Identifiers

PMID30977093
OpenAlexW2937507304

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.