Datasets created by members of the ORMIR community

Our datasets are on Zenodo grouped under the ORMIR community label. Here are their details:

Species	Anatomy	Content	Paper	Link to repository
Human	Trabecular bone (micro CT)	Segmented trabecular bone samples and corresponding distance tranforms	Abstract at QMSKI 2024	Zenodo
Human	Radius and tibia (HR-pQCT)	1 radius and 1 tibia acquired with standard protocol (82µ)	No publication available	Zenodo
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	Zenodo
Mouse	Knee (µCT)	22 images of trabecular bone at the proximal tibia	Lau A. et al. Joint bleeding in factor VIII deficient mice causes an acute loss of trabecular bone and calcification of joint soft tissues which is prevented with aggressive factor replacement	Zenodo
Synthetic data	Spheres, cylinders, and plates	Synthetic shapes for algorithm comparison	No publication available	Zenodo
Phantom data	Scanco XCTII - QC1 Phantom	Calibration density phantom for Xtreme CT II	No publication available	Zenodo

Dataset of MSK images available online

Species	Anatomy	Content	Paper	Link to repository
Human	Knee (MR)	Masks of bones and cartilages of about 500 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	ZIB
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	Stanford repository
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	ZIB
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.	ZIB
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	OSF
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	Spine generic