Open MSK images
ORMIR datasets¶
Here are the datasest created by members of the ORMIR community
Species |
Anatomy |
Image characteristics |
Corresponding paper |
Link to repository |
---|---|---|---|---|
Human |
Radius and tibia (HR-pQCT) |
1 radius and 1 tibia acquired with standard protocol (82µ) |
No publication available |
|
Human |
Knee (MR) |
About 100 OAI images with corresponding femoral cartilage masks, thicknesses, and relaxometry |
Bonaretti S. et al. pyKNEEr: An image analysis workflow for open and reproducible research on femoral knee cartilage |
|
Synthetic data |
Spheres, cylinders, and plates |
Synthetic shapes for algorithm comparison |
No publication available |
|
Mouse |
Knee (µCT) |
22 images of trabecular bone at the proximal tibia |
More datasets¶
Here are more dataset with MSK images
Species |
Anatomy |
Image characteristics |
Corresponding paper |
Link to repository |
---|---|---|---|---|
Human |
Knee (MR) |
Masks of bones and cartilages of about 600 images from the OAI dataset |
Ambellan F. et al. Automated segmentation of knee bone and cartilage combining statistical shape knowledge and convolutional neural networks: Data from the Osteoarthritis Initiative |
|
Human |
Knee (MR) |
1,370 knee MRI exams performed at Stanford University Medical Center. |
Bien N. et al. Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet |
|
Human |
Knee (MR) |
46996 automated segmentations of bones and cartilages from the OAI dataset |
Tack A. et al. Towards novel osteoarthritis biomarkers: Multi-criteria evaluation of 46,996 segmented knee MRI data from the Osteoarthritis Initiative |
|
Human |
Knee (MR) |
2399 automated MR knee menisci |
Tack A. et al. A deep multi-task learning method for detection of meniscal tears in MRI data from the Osteoarthritis Initiative database. |
|
Human |
Spine (CT) |
160 CT image series of 141 patients with segmentation masks of 1725 vertebrae |
Sekuboyina A. et al VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images |
|
Human |
Spine (MR) |
Collection of single subject datasets across 19 centers and multi-subject datasets across 42 centers (for a total of 260 participants), spanning different MRI manufacturers |
Cohen-Adad J. et al. Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers |