november, 2011

27novAll Day02decRSNA 2011

Event Details

On Monday November 28, Rick Avila and Wes Turner will be teaching two courses: ’Open Source Applications for Medical Imaging Research’ from 2:30-4:00 and ’Introduction to Open-Source Software Libraries for Medical Imaging’ from 4:30-6:00. The course descriptions can be found below.

Kitware will also be exhibiting in the Quantitative Imaging Reading room from November 27-December 2 in room S401CD, Booth LL-QRR-3009. The exhibit, ’The 3D Slicer open source software platform for segmentation, registration, quantitative analysis and 3D visualization of biomedical image data,’ will be attended by Jean-Christophe Fillion-Robin and Julien Finet each day from 12:15-1:15 for a meet-the-experts session.

’Open Source Applications for Medical Imaging Research’

Learning Objectives

This course is intended for those interested in an overview of the capabilities of existing, freely available, open-source, image analysis and visualization tools for medical and biomedical research. The objects are 1) Provide an overview of 3D Slicer the product of the National Alliance for Medical Image Computing (NA-MIC), an NIH Roadmap Initiative. 2) Provide a hands-on demonstration of the Interactive Scientific Publication system and VolViewISP. 3) Review the capabilities of other open-source applications and the toolkits upon which they are based. 4) Summarize licensing considerations in open-source software development and use.

Abstract

Open-source software and data sharing are changing the field of medical imaging research. In particular, the sharing of the algorithms and data of experiments, in addition to the publication of the articles that summarize the experiments, is leading to “reproducible science.” Reproducible science allows others to repeat published experiments, build upon them, and explore new applications of the algorithms. The pace of research is thereby greatly accelerated, and effective methods move more quickly from bench to bedside. This course presents select, freely available, open-source tools which have been developed and made available to facilitate reproducible science and medical image analysis research in general.

’Introduction to Open-Source Software Libraries for Medical Imaging’

 

Learning Objectives

This course is intended for managers, clinicians, researchers, and scientists who direct and/or conduct the development of new medical image analysis and display applications. It is intended to address the following: 1) Provide an overview of the open-source Insight Toolkit (ITK) and Visualization Tool (VTK). 2) Summarize the rigorous software practices which assure the functionality and stability of those toolkits.  3) Explore segmentation and registration algorithms in ITK for medical research and applications. 4) Explore visualization methods in VTK for medical research and applications. 5) Introduce web-based databases, that can also be integrated into desktop applications and workflows, for managing and distributing collections of data and associated publications. 6) Summarize licensing considerations in open-source software development and use.

Abstract

The field of medical image research and application is undergoing an explosion of scientific advancement, due in part to the spread of open source software. Herein we review two leading open-source, freely available software libraries for medical image analysis and visualization. The first is the Insight Toolkit (www.itk.org) which was funded by the National Institutes of Health, particularly the National Library of Medicine, to provide state-of-the-art medical image segmentation and registration algorithms. The second is the Visualization Toolkit (www.vtk.org) which provides leading medical image visualization techniques. We will also present the software policy and practices which assure the consistent quality of those toolkits. Furthermore, we review an open-source package for hosting multi-media (images, videos, presentations, and documents) associated with conducting, documenting, and distributing experiments and their data.

 

Time

November 27 (Sunday) - December 2 (Friday)

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