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Computational medical imaging and hemodynamics framework for functional analysis and assessment of cardiovascular structures

Overview of attention for article published in BioMedical Engineering OnLine, March 2017
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Title
Computational medical imaging and hemodynamics framework for functional analysis and assessment of cardiovascular structures
Published in
BioMedical Engineering OnLine, March 2017
DOI 10.1186/s12938-017-0326-y
Pubmed ID
Authors

Kelvin K. L. Wong, Defeng Wang, Jacky K. L. Ko, Jagannath Mazumdar, Thu-Thao Le, Dhanjoo Ghista

Abstract

Cardiac dysfunction constitutes common cardiovascular health issues in the society, and has been an investigation topic of strong focus by researchers in the medical imaging community. Diagnostic modalities based on echocardiography, magnetic resonance imaging, chest radiography and computed tomography are common techniques that provide cardiovascular structural information to diagnose heart defects. However, functional information of cardiovascular flow, which can in fact be used to support the diagnosis of many cardiovascular diseases with a myriad of hemodynamics performance indicators, remains unexplored to its full potential. Some of these indicators constitute important cardiac functional parameters affecting the cardiovascular abnormalities. With the advancement of computer technology that facilitates high speed computational fluid dynamics, the realization of a support diagnostic platform of hemodynamics quantification and analysis can be achieved. This article reviews the state-of-the-art medical imaging and high fidelity multi-physics computational analyses that together enable reconstruction of cardiovascular structures and hemodynamic flow patterns within them, such as of the left ventricle (LV) and carotid bifurcations. The combined medical imaging and hemodynamic analysis enables us to study the mechanisms of cardiovascular disease-causing dysfunctions, such as how (1) cardiomyopathy causes left ventricular remodeling and loss of contractility leading to heart failure, and (2) modeling of LV construction and simulation of intra-LV hemodynamics can enable us to determine the optimum procedure of surgical ventriculation to restore its contractility and health This combined medical imaging and hemodynamics framework can potentially extend medical knowledge of cardiovascular defects and associated hemodynamic behavior and their surgical restoration, by means of an integrated medical image diagnostics and hemodynamic performance analysis framework.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 66 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 18%
Researcher 8 12%
Student > Master 8 12%
Student > Bachelor 8 12%
Student > Doctoral Student 4 6%
Other 10 15%
Unknown 16 24%
Readers by discipline Count As %
Engineering 23 35%
Medicine and Dentistry 11 17%
Mathematics 3 5%
Nursing and Health Professions 2 3%
Unspecified 2 3%
Other 7 11%
Unknown 18 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 March 2017.
All research outputs
#18,539,663
of 22,961,203 outputs
Outputs from BioMedical Engineering OnLine
#563
of 824 outputs
Outputs of similar age
#235,447
of 309,329 outputs
Outputs of similar age from BioMedical Engineering OnLine
#6
of 14 outputs
Altmetric has tracked 22,961,203 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 824 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 16th percentile – i.e., 16% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 309,329 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.