Grigoris I. Grigoriadis - IEEE Xplore Author Profile

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The left atrium (LA) is one of the cardiac cavities with the most complex anatomical structures. Its role in the clinical diagnosis and patient's management is critical, as it is responsible for the atrial fibrillation, a condition that promotes the thrombogenesis inside the left atrial appendage. The development of an automated approach for LA segmentation is a demanding task mainly due to its an...Show More
Nowadays, there is a growing need for the development of computationally efficient virtual population generators for large-scale in-silico clinical trials. In this work, we utilize the Gaussian Mixture Models (GMM) with variational Bayesian inference (BGMM) using robust estimations of Dirichlet concentration priors for the generation of virtual populations. The estimations were based on an exponen...Show More
Left ventricular (LV) segmentation is an important process which can provide quantitative clinical measurements such as volume, wall thickness and ejection fraction. The development of an automatic LV segmentation procedure is a challenging and complicated task mainly due to the variation of the heart shape from patient to patient, especially for those with pathological and physiological changes. ...Show More
The SILICOFCM platform is an in-silico cloud computing platform which utilizes advanced computational workflows for drug development and optimized clinical therapy in the domain of hypertrophic cardiomyopathy (HCM). The current study presents the SILICOFCM’s virtual population model (VPM) which can be used to generate high-quality virtual clinical data using both multivariate and machine learning ...Show More
In this study, we developed and analyzed different patient-specific 3D anatomical models of the left atrium including left atrial Appendage, in order to investigate the local hemodynamics. Particularly, we focused on the left atrial appendage and its impact on thrombus formation due to wall shear stress alterations. A 3D semi-automated reconstruction approach was carried out to segment and reconst...Show More
In-silico clinical platforms have been recently used as a new revolutionary path for virtual patients (VP) generation and further analysis, such as, drug development. Advanced individualized models have been developed to enhance flexibility and reliability of the virtual patient cohorts. This study focuses on the implementation and comparison of three different methodologies for generating virtual...Show More