Evidence map›Paper›PMID 29769030›Full record

ArticleBMC medical imaging2018

In silico simulation of liver crack detection using ultrasonic shear wave imaging.

Erwei Nie, Jiao Yu, Debaditya Dutta, Yanying Zhu

Abstract read
In one paragraph

Article in BMC medical imaging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Erwei NieCollege of Information and Control Engineering, Liaoning Shihua University, Fushun, People's Republic of China.
Jiao YuCollege of Science, Liaoning Shihua University, Fushun, People's Republic of China. yujiaojoy@hotmail.com.
Debaditya DuttaSensing and Computer Vision, Union Pacific Railroad, Omaha, USA.
Yanying ZhuCollege of Science, Liaoning Shihua University, Fushun, People's Republic of China.

Funding

National Natural Science Foundation of China 11304137Program for Liaoning Excellent Talents in University LJQ2013042
6 · The paper itself

Abstract

backgroundLiver trauma is an important source of morbidity and mortality worldwide. A timely detection and precise evaluation of traumatic liver injury and the bleeding site is necessary. There is a need to develop better imaging modalities of hepatic injuries to increase the sensitivity of ultrasonic imaging techniques for sites of hemorrhage caused by cracks. In this study, we conduct an in silico simulation of liver crack detection and delineation using an ultrasonic shear wave imaging (USWI) based method.

methodsWe simulate the generation and propagation of the shear wave in a liver tissue medium having a crack using COMSOL. Ultrasound radio frequency (RF) signal synthesis and the two-dimensional speckle tracking algorithm are applied to simulate USWI in a medium with randomly distributed scatterers. Crack detection is performed using the directional filter and the edge detection algorithm rather than the conventional inversion algorithm. Cracks with varied sizes and locations are studied with our method and the crack localization results are compared with the given crack.

resultsOur pilot simulation study shows that, by using USWI combined with a directional filter cum edge detection technique, the near-end edge of the crack can be detected in all the three cracks that we studied. The detection errors are within 5%. For a crack of 1.6 mm thickness, little shear wave can pass through it and the far-end edge of the crack cannot be detected. The detected crack lengths using USWI are all slightly shorter than the actual crack length. The robustness of our method in detecting a straight crack, a curved crack and a subtle crack of 0.5 mm thickness is demonstrated.

conclusionsIn this paper, we simulate the use of a USWI based method for the detection and delineation of the crack in liver. The in silico simulation helps to improve understanding and interpretation of USWI measurements in a physical scattered liver medium with a crack. This pilot study provides a basis for improved insights in future crack detection studies in a tissue phantom or liver.

Indexed as

AlgorithmsComputer SimulationElasticity Imaging TechniquesFinite Element AnalysisHumansLiverPilot ProjectsUltrasonographyDirectional filterEdge detectionLiver crackSpeckle trackingUltrasonic shear wave imaging

Identifiers

PMID29769030
PMCPMC5956542

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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.