Anthony Kolasny

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The CardioVascular Research Grid (CVRG) Project’s goal is to facilitate research on heart disease through open-source informatics and data analysis tools, making it easier for researchers to manage, share, and analyze complex data collected in cardiovascular studies. Inefficient mechanisms for sharing and analyzing data hamper large studies and make it hard(More)
This article describes a large multi-institutional analysis of the shape and structure of the human hippocampus in the aging brain as measured via MRI. The study was conducted on a population of 101 subjects including nondemented control subjects (n = 57) and subjects clinically diagnosed with Alzheimer's Disease (AD, n = 38) or semantic dementia (n = 6)(More)
The schizophrenia research community has invested substantial resources on collecting, managing and sharing large neuroimaging datasets. As part of this effort, our group has collected high resolution magnetic resonance (MR) datasets from individuals with schizophrenia, their non-psychotic siblings, healthy controls and their siblings. This effort has(More)
The Computational Anatomy Gateway is a software as a service tool for medical imaging researchers to quantify changes in anatomical structures over time, and through the progression of disease. GPU acceleration on the Stampede cluster has enabled the development of new tools, combining advantages of grid based and particle based methods for describing fluid(More)
Computational Anatomy (CA) is a discipline focused on the quantitative analysis of the variability in biological shape. The Large Deformation Diffeomorphic Metric Mapping (LDDMM) is the key algorithm which assigns computable descriptors of anatomical shapes and a metric distance between shapes. This is achieved by describing populations of anatomical shapes(More)
This paper describes an automated procedure for creating detailed patient-specific pediatric dosimetry phantoms from a small set of segmented organs in a child's CT scan. The algorithm involves full body mappings from adult template to pediatric images using multichannel large deformation diffeomorphic metric mapping (MC-LDDMM). The parallel implementation(More)
Image analysis tools for brain magnetic resonance imaging (MRI) have become increasingly important for computer-aided diagnosis that involves large amounts of medical image data. The authors of this article have endeavored to develop software tools to serve the clinical research community, starting with a stand-alone executable, hybrid local computation(More)
Center for Imaging Science [1] B. Fischl,, Whole brain segmentation: automated labelling of neuroanatomical structures in the human brain, Neuron, 33:341, 2005. [2] M.F. Beg,, Computing Large Deformation Metric Mapping via Geodesic Flows of Diffeomorphisms, Int. J. Comp Vis, 61:139, 2005. [3] Venables, W.N. and Ripley, B.D.,(More)
This paper documents on-going work to facilitate ITK-based processing and 3D Slicer scene management in ParaView. We believe this will broaden the use of ParaView for high performance computing and visualization in the medical imaging research community. The effort is focused on developing ParaView plug-ins for managing VTK structures from 3D Slicer MRML(More)
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