Development of cloud services for patient-specific simulations of blood flows through aortic valves

Kačeniauskas, Arnas; Pacevič, Ruslan; Starikovičius, Vadimas; Maknickas, Algirdas; Staškźnienź, M.; Davidavičius, Giedrius

doi:10.1016/j.advengsoft.2016.01.013

Cited by 17 publications

(14 citation statements)

References 23 publications

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“…The velocity and pressure fields in the computational domain can be strongly affected by the outlet boundary conditions [5], therefore, various techniques including the proposed boundary condition were employed to handle the backflows occurring in the aortic valve flows. Time-consuming computations were performed by using the developed cloud software services [25,26] based on ANSYS Fluent [22]. Figure 4 shows the distribution of the velocity on the outlet in the case of various boundary conditions.…”

Section: Resultsmentioning

confidence: 99%

Investigation of the backflows and outlet boundary conditions for computations of the patient-specific aortic valve flows

Staškūnienė¹,

Kačeniauskas²,

Maknickas³

et al. 2018

THC

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Section: Resultsmentioning

confidence: 99%

Investigation of the backflows and outlet boundary conditions for computations of the patient-specific aortic valve flows

Staškūnienė¹,

Kačeniauskas²,

Maknickas³

et al. 2018

THC

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“…Recently, researchers have shown increased interest in studying and deploying container-based healthcare applications. Kačeniauskas et al [37] have developed a software to simulate blood flows through aortic valves, as a cloud service. They have experimentally evaluated the performance of XEN VMs, KVM VMs and Docker containers and have found that Docker containers outperform KVM and XEN VMs.…”

Section: Virtualisation Technologies In E-healthmentioning

confidence: 99%

Medical Data Processing and Analysis for Remote Health and Activities Monitoring

Vitabile

Marks

Stojanović

et al. 2019

Lecture Notes in Computer Science

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Recent developments in sensor technology, wearable computing, Internet of Things (IoT), and wireless communication have given rise to research in ubiquitous healthcare and remote monitoring of human's health and activities. Health monitoring systems involve processing and analysis of data retrieved from smartphones, smart watches, smart bracelets, as well as various sensors and wearable devices. Such systems enable continuous monitoring of patients psychological and health conditions by sensing and transmitting measurements such as heart rate, electrocardiogram, body temperature, respiratory rate, chest sounds, or blood pressure. Pervasive healthcare, as a relevant application domain in this context, aims at revolutionizing the delivery of medical services through a medical assistive environment and facilitates the independent living of patients. In this chapter, we discuss (1) data collection, fusion, ownership and privacy issues; (2) models, technologies and solutions for

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“…In this section, we presented the segmentation tool in clinical routine as well as a comparative study between two existing software which is in relief with the blood flow sequences and their limitations. A deep analysis of the development of cloud services or patient-specific simulations of blood flows through aortic valves based on ANSYS Fluent was mention in [36]. In this context, we can mention several works that use CFD modules with it can be deduced via the extraction of the parameters (the ratio between the outgoing and the incoming flow)…”

Section: B Flow Sequences and Valvesmentioning

confidence: 99%

Moving Towards a 5d Cardiac Model

Sakly¹,

Mahmoudi²,

Akil³

et al. 2019

J Flow Vis Image Proc

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The medical diagnosis process requires several steps to identify the types of cardiac pathologies. The segmentation step is used to determine the measurements for cardiac abnormalities on the short axis of the 4D acquired in MRI, but this phase remains limited on the blood flow sequences. The MRI modality allow to the experts to quantify the stenosis and the regurgitation of aortic blood flow. The parameters extracted from the flow sequences, after segmentation, make it possible to identify the valvular pathologies, but they are not sufficient to complete the medical prognosis as well as the lack of precision of these measurements. In this paper, we propose to make a coupling between the 4D cardiac cuts with their study of blood flow through the technique of registration and reconstruction. The interest of the purpose of the blood flow as fifth dimension is to improve the accuracy of the cardiac parameters and the extracting of measurements for valvulopathies in the process of assistance to the decision for the experts An example was introduced in this context through the development of cloud services for patient-specific simulations of blood flows through aortic valves as well as an OsiriX software for 5D visualization that combines a 4D sequence and the functional flow dimension. In this framework, we proposed a processing chain to lead towards a 5D solution. Another problem is raised is the choice of the appropriate architecture to solve the problem of hybrid parallelization for the processing of these cardiac images. To test the constraints of time of the concept of 5D, we need a GPU graphics processor acquired in MRI, as well as a CPU processor to perform the complexity of calculation and the operations applied to the algorithms of image processing.

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Development of cloud services for patient-specific simulations of blood flows through aortic valves

Cited by 17 publications

References 23 publications

Investigation of the backflows and outlet boundary conditions for computations of the patient-specific aortic valve flows

Investigation of the backflows and outlet boundary conditions for computations of the patient-specific aortic valve flows

Medical Data Processing and Analysis for Remote Health and Activities Monitoring

Moving Towards a 5d Cardiac Model

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