Welcome to the Mild Traumatic Brain Injury Outcome Prediction (mTOP) challenge. Its aim is to create a common ground to compare methods to find predictive MRI features, which help to characterise and distinguish mild traumatic brain injury patients from each other and healthy subjects.
Together with the BRATS and ISLES challenges, mTOP will be part of the Brainles workshop (17th October), which will be held at the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2016.
Please find further information below or on the mTOP webpage.
First time users will have to register, selecting MTOP2016 as research unit in the process. If you already have an account with SMIR, navigate to Group Administration and select "Join another research unit" to join MTOP2016. In both cases, you will have to wait until your registration is confirmed by an administrator
Participant will have to assign a cluster label (1/2/3) to each subject. Methods will be evaluated by their:
Adjusted Rand Index – Similarity of two assignments (submitted cluster labels vs. ground truth), which is invariant to permutations and normalised to chance.
Homogeneity – Purity of ground truth labels within cluster.
A rank per team is established for each measurement, separately. The mean rank of both metric ranks is then the team’s final rank, which will determine the winner.
A participation in mTOP requires the submitting team to write a short paper of 4 pages (LNCS format). This will be reviewed by the organisers w.r.t.: - Clear and detailed description of applied methods - Listing of all parameter values and employed frameworks - Description of data set must not be included - Motivation for chosen method is appreciated
Please send a PDF (with standard fonts) until 12th August 2016 – 23:59 GMT with subject: "mTOP2016" and your team name. Final results will be published on the webpage.
Talk: Three selected methods will be invited to give an oral presentation (10mins + questions). Selected teams will be announced directly after the evaluation round.
Poster: Each participating team is invited to present their work as a poster
The data set is provided by the Division of Anaesthesia at Addenbrookes Hospital, University of Cambridge.
Please reference the SMIR - The Virtual Skeleton Database in your work as:
Please register to access the download section