{"id":2436,"date":"2024-05-03T16:35:35","date_gmt":"2024-05-03T16:35:35","guid":{"rendered":"https:\/\/labs.cs.queensu.ca\/perklab\/members\/csaba-pinter\/"},"modified":"2024-05-03T16:35:35","modified_gmt":"2024-05-03T16:35:35","slug":"csaba-pinter","status":"publish","type":"qsc_member","link":"https:\/\/labs.cs.queensu.ca\/perklab\/members\/csaba-pinter\/","title":{"rendered":"Csaba Pinter"},"content":{"rendered":"
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Csaba Pinter<\/h1>\n<\/div>\n
Staff<\/div>\n
School of Computing<\/div>\n
Queen’s University<\/div>\n
Member from 2011<\/em> to 2019<\/em><\/div>\n
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\n\tCsaba Pinter graduated at the University of Szeged, Hungary in 2006 as Computer Program Designer (MSc in Image Processing). He participated various medical image processing related research projects first at the university, then in the industry at companies in the field of radiology, nuclear medicine, and digital microscopy. His main interests are medical image segmentation and the design of innovative medical applications.
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83 entries<\/span> «<\/a> ‹<\/a> 1 of 2 ›<\/a> »<\/a> <\/div><\/div>

Lasso, Andras; Herz, Christian; Nam, Hannah; Cianciulli, Alana; Pieper, Steve; Drouin, Simon; Pinter, Csaba; St-Onge, Samuelle; Vigil, Chad; Ching, Stephen; Sunderland, Kyle; Fichtinger, Gabor; Kikinis, Ron; Jolley, Matthew A<\/p>

SlicerHeart: An open-source computing platform for cardiac image analysis and modeling<\/a> Journal Article<\/span> <\/p>

In: <\/span>vol. 9, <\/span>pp. 886549, <\/span>2022<\/span>.<\/p>

Abstract<\/a><\/span> | Links<\/a><\/span> | BibTeX<\/a><\/span><\/p>

@article{fichtinger2022c,
\r\ntitle = {SlicerHeart: An open-source computing platform for cardiac image analysis and modeling},
\r\nauthor = {Andras Lasso and Christian Herz and Hannah Nam and Alana Cianciulli and Steve Pieper and Simon Drouin and Csaba Pinter and Samuelle St-Onge and Chad Vigil and Stephen Ching and Kyle Sunderland and Gabor Fichtinger and Ron Kikinis and Matthew A Jolley},
\r\nurl = {https:\/\/www.frontiersin.org\/articles\/10.3389\/fcvm.2022.886549\/full},
\r\nyear  = {2022},
\r\ndate = {2022-01-01},
\r\nvolume = {9},
\r\npages = {886549},
\r\npublisher = {Frontiers},
\r\nabstract = {Cardiovascular disease is a significant cause of morbidity and mortality in the developed world. 3D imaging of the heart\u2019s structure is critical to the understanding and treatment of cardiovascular disease. However, open-source tools for image analysis of cardiac images, particularly 3D echocardiographic (3DE) data, are limited. We describe the rationale, development, implementation, and application of SlicerHeart, a cardiac-focused toolkit for image analysis built upon 3D Slicer, an open-source image computing platform. We designed and implemented multiple Python scripted modules within 3D Slicer to import, register, and view 3DE data, including new code to volume render and crop 3DE. In addition, we developed dedicated workflows for the modeling and quantitative analysis of multi-modality image-derived heart models, including heart valves. Finally, we created and integrated new functionality to facilitate the planning of cardiac interventions and surgery. We demonstrate application of SlicerHeart to a diverse range of cardiovascular modeling and simulation including volume rendering of 3DE images, mitral valve modeling, transcatheter device modeling, and planning of complex surgical intervention such as cardiac baffle creation. SlicerHeart is an evolving open-source image processing platform based on 3D Slicer initiated to support the investigation and treatment of congenital heart disease. The technology in SlicerHeart provides a robust foundation for 3D image-based investigation in cardiovascular medicine.},
\r\nkeywords = {},
\r\npubstate = {published},
\r\ntppubtype = {article}
\r\n}
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Cardiovascular disease is a significant cause of morbidity and mortality in the developed world. 3D imaging of the heart\u2019s structure is critical to the understanding and treatment of cardiovascular disease. However, open-source tools for image analysis of cardiac images, particularly 3D echocardiographic (3DE) data, are limited. We describe the rationale, development, implementation, and application of SlicerHeart, a cardiac-focused toolkit for image analysis built upon 3D Slicer, an open-source image computing platform. We designed and implemented multiple Python scripted modules within 3D Slicer to import, register, and view 3DE data, including new code to volume render and crop 3DE. In addition, we developed dedicated workflows for the modeling and quantitative analysis of multi-modality image-derived heart models, including heart valves. Finally, we created and integrated new functionality to facilitate the planning of cardiac interventions and surgery. We demonstrate application of SlicerHeart to a diverse range of cardiovascular modeling and simulation including volume rendering of 3DE images, mitral valve modeling, transcatheter device modeling, and planning of complex surgical intervention such as cardiac baffle creation. SlicerHeart is an evolving open-source image processing platform based on 3D Slicer initiated to support the investigation and treatment of congenital heart disease. The technology in SlicerHeart provides a robust foundation for 3D image-based investigation in cardiovascular medicine.<\/div>
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