@article{,
title= {Ischemic Stroke Lesion Segmentation Challenge 2017 (ISLES2017)},
keywords= {},
journal= {},
author= {},
year= {2017},
url= {http://www.isles-challenge.org/},
license= {Open Database License},
abstract= {Ischemic Stroke Lesion Segmentation (ISLES), a medical image segmentation challenge at the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2017. On the SMIR, you can register for the challenge, download the test data and submit your results. For more information, visit the official ISLES homepage under www.isles-challenge.org.

### THE ISLES CHALLENGE

This challenge for stroke lesions segmentation has been very popular the past two years (2015, 2016) and yielded various methods, that help to tackle important challenges of modern stroke imaging analysis. This year the challenge provides acute stroke imaging scans and manually outlined lesions on follow-up scans.

### HOW IT WORKS

If you are interested in participating, you are invited to download the training set, including both MRI scans as well as the corresponding expert segmentations of stroke lesions. This will allow you to validate and optimise your method as much as you favour.

Shortly before MICCAI 2017 will take place, a set of test cases will be released of which participants will be asked to run their algorithm on and upload their segmentation results in form of binary image maps. To complete a successful participation, participants will need to submit an abstract, describing the employed method.

The organizers will then evaluate each case and establish a ranking of the participating teams. All results will be presented during SWITCH at MICCAI 2017 and will be discussed with invited experts and all workshop attendees.

Each team will have the opportunity to present their submitted method as a poster, while selected teams will be asked to give a brief presentation detailing their approach. Eventually, submissions will be included in the workshops LNCS post-proceedings and potentially compiled for a high-impact journal paper to summarise and present the findings.


### Please cite the challenge article if you use the data:

Oskar Maier et al.
        ISLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI
        Medical Image Analysis, Available online 21 July 2016, ISSN 1361-8415
        http://dx.doi.org/10.1016/j.media.2016.07.009. 
        
Kistler et al. 
        The virtual skeleton database: an open access repository for biomedical research and collaboration. JMIR, 2013
        http://doi.org//10.2196/jmir.2930
        },
superseded= {},
terms= {}
}