5 citations · 7 across the 5 of their papers we have counts for
6 papers
Near Real-time Adaptive Isotropic and Anisotropic Image-to-mesh Conversion for Numerical Simulations Involving Cerebral Aneurysms
Kevin Garner, Fotis Drakopoulos, Chander Sadasivan +1
Presented are two techniques that are designed to help streamline the discretization of complex vascular geometries within the numerical modeling process. The first method integrat…
Image-To-Mesh Conversion for Biomedical Simulations
Fotis Drakopoulos, Kevin Garner, Christopher Rector +1
Converting a three-dimensional medical image into a 3D mesh that satisfies both the quality and fidelity constraints of predictive simulations and image-guided surgical procedures…
Real-Time Dynamic Data Driven Deformable Registration for Image-Guided Neurosurgery: Computational Aspects
Nikos Chrisochoides, Andrey Fedorov, Yixun Liu +10
Current neurosurgical procedures utilize medical images of various modalities to enable the precise location of tumors and critical brain structures to plan accurate brain tumor re…
Advancing Intra-operative Precision: Dynamic Data-Driven Non-Rigid Registration for Enhanced Brain Tumor Resection in Image-Guided Neurosurgery
Nikos Chrisochoides, Andriy Fedorov, Fotis Drakopoulos +9
During neurosurgery, medical images of the brain are used to locate tumors and critical structures, but brain tissue shifts make pre-operative images unreliable for accurate remova…
Convolutional Auto-Encoders for Drift Chamber data de-noising for CLAS12
Gagik Gavalian, Polykarpos Thomadakis, Angelos Angelopoulos +1
In this article, we present the results of using Convolutional Auto-Encoders for de-noising raw data for CLAS12 drift chambers. The de-noising neural network provides increased eff…
CLAS12 Track Reconstruction with Artificial Intelligence
Gagik Gavalian, Polykarpos Thomadakis, Angelos Angelopoulos +3
In this article we describe the implementation of Artificial Intelligence models in track reconstruction software for the CLAS12 detector at Jefferson Lab. The Artificial Intellige…