The MRNet dataset consists of 1,370 knee MRI exams performed at Stanford University Medical Center. The dataset contains 1,104 (80.6%) abnormal exams, with 319 (23.3%) ACL tears and 508 (37.1%) meniscal tears; labels were obtained through manual extraction from clinical reports. The dataset accompanies the publication of the MRNet work here.
The most common indications for the knee MRI examinations in this study included acute and chronic pain, follow-up or preoperative evaluation, injury/trauma. Examinations were performed with GE scanners (GE Discovery, GE Healthcare, Waukesha, WI) with standard knee MRI coil and a routine non-contrast knee MRI protocol that included the following sequences: coronal T1 weighted, coronal T2 with fat saturation, sagittal proton density (PD) weighted, sagittal T2 with fat saturation, and axial PD weighted with fat saturation. A total of 775 (56.6%) examinations used a 3.0-T magnetic field; the remaining used a 1.5-T magnetic field. See our paper for more details.
The exams have been split into a training set (1,130 exams, 1,088 patients), a validation set (called tuning set in the paper) (120 exams, 111 patients), and a hidden test set (called validation set in the paper) (120 exams, 113 patients). To form the validation and tuning sets, stratified random sampling was used to ensure that at least 50 positive examples of each label (abnormal, ACL tear, and meniscal tear) were present in each set. All exams from each patient were put in the same split.
The leaderboard reports the average AUC of the abnormality detection, ACL tear, and Meniscal tear tasks.
|1 ||Jan 09, 2019||mrnet-baseline (single model) Stanford University||0.917|
|2 ||May 28, 2019||dc_baseline(single model) Mason High||0.911|
|3 ||May 29, 2019||Triple-MRNet (single model) Independent Researcher https://github.com/yashbhalgat/MRNet-Competition||0.904|
|4 ||Apr 27, 2019||IL_baseline (single model) Stanford Alum||0.900|
We are hosting a competition to encourage others to develop models for automated interpretation of knee MRs. Our test set (called internal validation set in the paper) has its ground truth set using the majority vote of 3 practicing board-certified MSK radiologists (years in practice 6–19 years, average 12 years). The MSK radiologists had access to all DICOM series, the original report and clinical history, and follow-up exams during interpretation.
MRNet uses a hidden test set for official evaluation of models. Teams submit their executable code on Codalab, which is then run on a test set that is not publicly readable. Such a setup preserves the integrity of the test results.
Here's a tutorial walking you through official evaluation of your model. Once your model has been evaluated officially, your scores will be added to the leaderboard.
Please read the Stanford University School of Medicine MRNet Dataset Research Use Agreement. Once you register to download the MRNet dataset, you will receive a link to the download over email. Note that you may not share the link to download the dataset with others.
1. Permission is granted to view and use the MRNet Dataset without charge for personal, non-commercial research purposes only. Any commercial use, sale, or other monetization is prohibited.
2. Other than the rights granted herein, the Stanford University School of Medicine (“School of Medicine”) retains all rights, title, and interest in the MRNet Dataset.
3. You may make a verbatim copy of the MRNet Dataset for personal, non-commercial research use as permitted in this Research Use Agreement. If another user within your organization wishes to use the MRNet Dataset, they must register as an individual user and comply with all the terms of this Research Use Agreement.
4. YOU MAY NOT DISTRIBUTE, PUBLISH, OR REPRODUCE A COPY of any portion or all of the MRNet Dataset to others without specific prior written permission from the School of Medicine.
5. YOU MAY NOT SHARE THE DOWNLOAD LINK to the MRNet dataset to others. If another user within your organization wishes to use the MRNet Dataset, they must register as an individual user and comply with all the terms of this Research Use Agreement.
6. You must not modify, reverse engineer, decompile, or create derivative works from the MRNet Dataset. You must not remove or alter any copyright or other proprietary notices in the MRNet Dataset.
7. The MRNet Dataset has not been reviewed or approved by the Food and Drug Administration, and is for non-clinical, Research Use Only. In no event shall data or images generated through the use of the MRNet Dataset be used or relied upon in the diagnosis or provision of patient care.
8. THE MRNet DATASET IS PROVIDED "AS IS," AND STANFORD UNIVERSITY AND ITS COLLABORATORS DO NOT MAKE ANY WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS MRNet DATASET.
9. You will not make any attempt to re-identify any of the individual data subjects. Re-identification of individuals is strictly prohibited. Any re-identification of any individual data subject shall be immediately reported to the School of Medicine.
10. Any violation of this Research Use Agreement or other impermissible use shall be grounds for immediate termination of use of this MRNet Dataset. In the event that the School of Medicine determines that the recipient has violated this Research Use Agreement or other impermissible use has been made, the School of Medicine may direct that the undersigned data recipient immediately return all copies of the MRNet Dataset and retain no copies thereof even if you did not cause the violation or impermissible use.
In consideration for your agreement to the terms and conditions contained here, Stanford grants you permission to view and use the MRNet Dataset for personal, non-commercial research. You may not otherwise copy, reproduce, retransmit, distribute, publish, commercially exploit or otherwise transfer any material.
You may use MRNet Dataset for legal purposes only.
You agree to indemnify and hold Stanford harmless from any claims, losses or damages, including legal fees, arising out of or resulting from your use of the MRNet Dataset or your violation or role in violation of these Terms. You agree to fully cooperate in Stanford’s defense against any such claims. These Terms shall be governed by and interpreted in accordance with the laws of California.