CALL FOR PAPERS

          MICCAI Workshop on 3D Segmentation in the Clinic
                        - A Grand Challenge -

                       Oct 29 or Nov 02, 2007
                         Brisbane, Australia

          http://mbi.dkfz-heidelberg.de/grand-challenge2007

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We would like to invite you to the first public contest and evaluation
of 3D segmentation methods in medical image analysis:
Tune your algorithm on supplied training data, evaluate it on specific
test images and get objective results, to be compared to all other
submissions - will you join the challenge?


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This workshop presents a contest for automatic segmentation methods in
two ambitious and relevant applications of medical image analysis:
The 3D segmentation of the caudate nucleus in brain MRI images and of
the liver in abdominal CT images.

After signing a letter of intent, participants can download training
datasets (with manual reference segmentations) from a designated website
in order to train and tune their algorithms. To qualify for the
challenge, authors have to run their algorithms on a first set of
supplied test data and upload the resulting segmentations. The results
(numbers, tables and figures) will be mailed back and must be included
in the paper.

The main competition will take place on an additional set of unseen test
datasets, either live at the workshop (if participants run the
segmentation on their own laptops) or in advance by the organizers (if
participants send in executables of their algorithms on supported
platforms). Results will be compared with manual reference segmentations
using a number of evaluation metrics; they will be ranked and presented
for the first time at the workshop. The winners of each category will be
awarded with small prizes, and endless fame and glory.

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We are open for submission of letters of intent to participate now,
please see our website http://mbi.dkfz-heidelberg.de/grand-challenge2007
for the necessary documents and details of the process.


Best regards from the workshop organizers:

Tobias Heimann     Medical and Biological Informatics,
                    German Cancer Research Center, Germany
Bram van Ginneken  Image Sciences Institute,
                    University Medical Center Utrecht, The Netherlands
Martin Styner      Neuro Image Analysis Laboratory,
                    University of North Carolina at Chapel Hill, USA



                      Join the challenge now!