We are excited to announce the workshop for Image-Guided Adaptive Radiation Therapy (IGART), which is held in conjunction with the Medical Image Computing and Computer Assisted Interventions (MICCAI) conference (www.miccai2017.org) in Quebec City, Canada. The workshop aims at presenting leading edge applications of medical image computing in the field of radiation therapy. The workshop provides an invaluable opportunity to present and discuss recent and preliminary research in this exciting field, in addition to providing a good forum to get constructive feedback from fellow researchers on more developed pieces of work.
The workshop will consist of two parts. The first, longer part will be a series of oral presentations by invited experts in the field and authors of the submitted papers accepted for presentation, where the participants learn about relevant novel algorithms, methods and software toolkits. The second, shorter part will consist of a software demo featuring selected open-source software toolkits supporting IGART research workflows.
The workshop is scheduled for Thursday, September 14, 2017. Feel free to contact us at igart@miccai2017.org.
Submission of manuscripts (extended): June 25, 2017
Notification of acceptance: July 16, 2017
Camera-ready papers: Aug 6, 2017
Early bird registration: August 14, 2017 (note that the workshop may be cancelled if less than 20 attendees have registered at that time).
Preliminary program (details TBA):
Cancer is a leading cause of death worldwide. One of the most common types of cancer treatment is radiation therapy. Given the non-invasive nature of radiotherapy, images and image computing form the basis for radiation therapy. Examples range from pre-treatment delineation of the target region to intra-treatment tracking of tissue motion and deformation. Thus, the workshop presents an interesting forum for researchers from the MIC and CAI parts of the community. The applications in radiation therapy have frequently been a driving force in the development of new image computing algorithms.
Tumors treated with radiotherapy are typically located in the cervical, thoracic and pelvic regions, as well as, the brain. The processing commonly requires the registration and segmentation of images. Registration is used for motion estimation and positioning, as well as for supporting atlas-based segmentation. The segmentation of the tumor region and organs at risk is important for the creating the radiation plan and monitoring the administered dose. A variety of image modalities can be involved in this processing, e.g. CT (kV, MV, cone-beam), PET, MR, DTI, and OCT. Next to algorithmic novelties, also submissions describing recent software toolkits are welcome.
We accept submissions ranging from extended abstract (2 pages) to full papers (8 pages) in PDF format. The review is single-blind, so please list the authors with their affiliations on the submission.
Papers can be subbmitted through the EasyChair submission system.
Massachusetts General Hospital and Harvard Medical School
Department of Physics, Queen’s University, Kingston, Ontario, Canada
Department of Medical Physics, Cancer Centre of Southeastern Ontario at Kingston General
Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Austria and
Christian-Doppler Laboratory for Medical Radiation Research for Radiation Oncology
Laboratory for Percutaneous Surgery, School of Computing, Queen’s University