3D Segmentation in the Clinic: A Grand Challenge II: MS lesion segmentation
logo

Please use this identifier to cite or link to this publication: http://hdl.handle.net/10380/1509
This paper describes the setup of a segmentation competition for the automatic extraction of Multiple Sclerosis (MS) lesions from brain Magnetic Resonance Imaging (MRI) data. This competition is one of three competitions that make up a comparison workshop at the 2008 Medical Image Computing and Computer Assisted Intervention (MICCAI) conference and was modeled after the successful comparison workshop on liver and caudate segmentation at the 2007 MICCAI conference. In this paper, the rationale for organizing the competition is discussed, the training and test data sets for both segmentation tasks are described and the scoring system used to evaluate the segmentation is presented.

Reviews
There is no review at this time. Be the first to review this publication!

Quick Comments
Comment by Abdelkhalek Bakkari yellow
I would be grateful if you could submit the source code of the proposed approach.


Resources
backyellow
Download All

Statistics more
backyellow
Global rating: starstarstarstarstar
Review rating: starstarstarstarstar [review]
Paper Quality: plus minus
1 comment

Information more
backyellow
Categories: Classification, Segmentation, Unsupervised learning and clustering
Keywords: MS lesions, Lesion segmentation, MRI, Segmentation evaluation
Export citation:

Share
backyellow
Share

Linked Publications more
backyellow
N4ITK:  Nick's N3 ITK Implementation For MRI Bias Field Correction N4ITK: Nick's N3 ITK Implementation For MRI Bias Field Correction
by Tustison N., Gee J.
3D Slicer Based Surgical Robot Console System 3D Slicer Based Surgical Robot Console System
by Yamada A., Nishibori K., Hayashi Y., Tokuda J., Hata N., Chinzei K., Fujimoto H.

View license
Loading license...

Send a message to the author
main_flat
Powered by Midas