Child pages
  • NCI-MICCAI 2013 Grand Challenges in Image Segmentation

You are viewing an old version of this page. View the current version.

Compare with Current View Page History

« Previous Version 4 Next »

Summary

The Cancer Imaging Program of the National Cancer Institute (NCI) in collaboration with the 16th international conference on Medical Image Computing and Computer Assisted Interventions (MICCAI 2013) have launched two grand challenges in segmentation of clinically relevant prostate structures and brain tumor components based on magnetic resonance imaging (MRI) data. The event will take place at MICCAI 2013 meeting (http://www.miccai2013.org/) on September 22 in Nagoya, Japan. 

Automated Segmentation of Prostate Structures (ASPS): Magnetic resonance imaging (MRI) is the clinically accepted modality for staging extra capsular extension and thus a key modality for image-guided interventions of the prostate.  The accuracy of such interventions may be improved by automated segmentation of the prostate capsule and clinically relevant internal structures.  The overall goal of the prostate challenge is to promote the development of robust algorithms that automatically segment the neurovascular bundle and seminal vesicles from clinical images.

Multiparametric Brain Tumor Segmentation (BRATS): Segmentation of brain tumors is a critical step in treatment planning and evaluation of response to therapy.  It is also one of the most challenging tasks in medical image analysis, due to the variable shape and heterogeneity of such tumors. Magnetic resonance imaging (MRI) provides a rich and diverse data set to study brain tumors.  Multicenter data will be used for segmentation of four tumor subregions, while inter-reader agreement from clinicians will be used as a benchmark for comparing the algorithm.

Each challenge will be based on a collection of 60 de-identified clinical cases, with expert annotations.  Initially the contestants may access 40 training cases with annotations.  Several weeks before the meeting they may upload segmentation of Leader Board cases (10) to allow computation of scores as feedback.  Contestants will be granted access to the sequestered challenge (test) data (10) at the beginning of the workshop.  In the first half of the workshop participants process the data and report their scores.  Testing of open and closed source solutions will be run in parallel.  In the second half of the workshop the scores are posted and presentations are given. 

Email questions to: imaging.challenge@nih.gov

Challenge Structure and Time Line

  1. May 24: Training data release
  2. July 2: Challenge Abstracts Due
  3. July 22: MICCAI Early registration deadline
  4. August 23: Leader Board release
  5. September 22: On-site NCI-MICCAI Challenges: BRATS & ASPS

Participating in the Challenges

Please see the following information about how to obtain the data and begin participating in the two challenges:

Automated Segmentation of Prostate Structures (ASPS)

Participants can access the data and instructions via NCI-MICCAI 2013 Challenge - Automated Segmentation of Prostate Structures.

Multiparametric Brain Tumor Segmentation (BRATS)

Participants can access the data and instructions via the Virtual Skeleton Database (VSD) at: http://www.virtualskeleton.ch/. Click the submenu "BRATS"->2013 to get started.

Organizers & Major Contributors

Stephen Aylward, Kitware Inc. (stephen.aylward@kitware.com)
Nicholas Bloch, Boston University (nicolas.bloch@me.com)
Larry Clarke, NCI (lclarke@mail.nih.gov)
Andinet Enquobahrie, Kitware Inc. (andinet.enqu@kitware.com)
Keyvan Farahani, NCI (Farahani@nih.gov)
John Freymann, SAIC-Frederick (freymanj@mail.nih.gov)
Elizabeth Gerstner, MGH/Harvard Medical School (egerstner@partners.org)
Henkjan Huisman, Radboud University (h.huisman@rad.umcn.nl)
Carl Jaffe, Boston University (carljaffe@gmail.com)
Jayashree Kalpathy-Cramer, Harvard Medical School (kalpathy@nmr.mgh.harvard.edu)
Justin Kirby, SAIC-Frederick (kirbyju@mail.nih.gov)
Anant Madabhushi, Case Western Reserve University (anant.madabhushi@case.edu)
Bjoern Menze, ETH Zurich (bjoern@ethz.ch)
Mauricio Reyes, University of Bern (mauricio.reyes@istb.unibe.ch)

  • No labels