Sonia Marie-Aurore Pujol PhD, Presenter: Nothing to Disclose

Katarzyna J. Macura MD, PhD, Presenter: Nothing to Disclose

Ron Kikinis MD, Presenter: Nothing to Disclose

1) Enhance interpretation of DICOM images through the use of 3D visualization. 2) Gain hands-on experience with quantitative imaging tools developed in clinical research. 3) Present current directions of quantitative imaging biomarkers in clinical trials.

Quantitative imaging has the potential to bring valuable information for the assessment of treatment response. Technological breakthroughs in medical imaging hardware and the emergence of increasingly sophisticated image processing algorithms permit the estimation of quantitative parameters with increasing sensitivity and specificity. For the past 10 years, the National Alliance for Medical Image Computing (NA-MIC), one of the seven National Centers for Biomedical Computing funded by the National Institutes of Health, has converted some of the major scientific advances made by the biomedical imaging community into open-source software tools. As part of the NA-MIC toolkit, the 3D Slicer open-source software has been developed as a technology delivery platform for clinical researchers. The course provides an introduction to quantitative medical imaging data analysis and includes a series of hands-on sessions using 3D Slicer. Cases from multiple imaging modalities and from multiple organ systems will be highlighted to illustrate the depth and breath of this field. The hands-on sessions will give participants a practical experience of the latest quantitative image analysis tools developed in clinical research. Course url: http://www.na-mic.org/Wiki/index.php/RSNA_2014

http://www.na-mic.org/Wiki/index.php/RSNA_Quantitative_Imaging_Course

Pujol, S, Macura, K, Kikinis, R, Slicer: Quantitative Medical Imaging for Clinical Research and Practice (Hands-on).  Radiological Society of North America 2014 Scientific Assembly and Annual Meeting, - ,Chicago IL. http://archive.rsna.org/2014/11033044.html