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Computational Biomechannics Platform for Diagnosis and Prediction of Cardiovascular Diseases (MS Thesis)

By: Contributor(s): Material type: TextPublication details: Nawabshah; QUEST; 2018Description: 127Online resources:
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Cover image Item type Current library Home library Collection Shelving location Call number Materials specified Vol info URL Copy number Status Notes Date due Barcode Item holds Item hold queue priority Course reserves
Thesis and Dissertation Research Section Available MP/53-659
Thesis and Dissertation Research Section Available MP/38-411
Thesis and Dissertation Research Section Available MP/34-370
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ABSTRACT

In the past few years, mortality has slightly decreased but not has morbidity. This is because we are having improper understanding and limited tools towards the causes of cardiovascular diseases. Observing these facts, the latest treatment method needs to be adopted by the medical sector for fighting against CVDs. Furthermore, there is a need to facilitate medical personnel and clinicians with an easy and optimal approach using computer-based intervention for cardiovascular diagnosis and treatment. The idea is to have a better insight into diagnosis, visualisation and simulation of the patient-specific post and pre-operative surgical procedures and follow-ups.

This project presents a novel framework to automate cardiovascular disease diagnosis/analysis and prognosis using computational biomechanics to assist cardiac professionals in taking optimal decisions in treatment management and surgical interventions. It aims to replace the conventional diagnostic procedure which depends mainly on human expertise and is very time-consuming. This research incorporates the use of digital image segmentation, digital image modelling and computational fluid dynamics to simulate blood dynamics for near-realistic simulations of physical factors of blood inside vascular structures. In this thesis, three geometrical models of the abdominal aorta and femoral arteries with stenosis and bypass graft are studied and real data which are obtained from PCMRI are compared with the numerically simulated results to show the accuracy of the project methodology. The average flow obtained from numerical simulation in the bypass graft is 8.9mL/s whereas the measured flow values of PCMRI is 9.3mL/s with the absolute difference of 0.40 ± 0.28 mL/s in the flow waveform. Comparing the measurements obtained from PCMRI with
the computational results of the average flow at the proximal region of occlusion was 4.0mL/s as compared to values of numerical simulation 4.6mL/s with the absolute difference of 0.66 ± 0.42 mL/s in the flow waveform. The computational simulations and the PC-MRI show the similar shape and amplitudes of the flow rate waveform s with a minor variation.

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