Sites that list and/or host multiple collections of data:

• The Cancer Imaging Archive (TCIA) formerly the National Biomedical Imaging Archive (NBIA):
• Lung Image Database Consortium (LIDC)
• Reference Image Database to Evaluate Response (RIDER)
• Breast MRI
• Lung PET/CT
• Neuro MRI
• CT Colongraphy
• Virtual Colonoscopy
• Osteoarthritis Initiative (MIA)
• PET/CT phantom scan collection
• OASIS
• Cross-sectional MRI Data in Young, Middle Aged, Nondemented and Demented Older Adults
• Longitudinal MRI Data in Nondemented and Demented Older Adults
• ADNI
• Alzheimer’s Disease Neuroimaging Initiative (ADNI) unites researchers with study data as they work to define the progression of Alzheimer’s disease. ADNI researchers collect, validate and utilize data such as MRI and PET images, genetics, cognitive tests, CSF and blood biomarkers as predictors for the disease.
• FITBIR
• The Federal Interagency Traumatic Brain Injury Research (FITBIR) informatics system: MRI, PET, Contrast, and other data on a range of TBI conditions
• STARE
• STructured Analysis of the Retina: This research concerns a system to automatically diagnose diseases of the human eye.
• Cancer Digital Slide Archive
• Whole-slide images from The Cancer Genome Atlas's (TCGA) glioblastoma multiforme (GBM) samples
  
• The Cancer Imaging Archive
• The image data in The Cancer Imaging Archive (TCIA) is organized into purpose-built collections of subjects. The subjects typically have a cancer type and/or anatomical site (lung, brain, etc.) in common.
• Johns Hopkins Medical Institute
• DTI Atlases: adults, children, ...
• Duke Center for In Vivo Microscopy
• Small animal MRI, CT, ...
• MIDAS
• National Alliance for Medical Image Computing (NAMIC)
• Lupus white matter lesions
• Brain MRI: 2-4 years old
• Prostate
• NLM: Imaging Methods Assessment and Reporting
• Liver tumors with segmentations
• 100 Healthy Brain MRI: 18-90 years old
• UCI Machine Learning Repository: The father of internet data archives for all forms of machine learning.
• Computer Vision Online Image Archive
• Large listing of multiple databases in computer vision and biomedical imaging
• Cornell Visualization and Image Analysis (VIA) group: Provides a list of available databases, many of which are also listed here.
• UT Health Science Center Image Collections: List of medical images, atlases, and databases available on the web.
• OmniMedicalSearch.com: Medical Image Databases & Libraries
• Digital Database for Screening Mammography (DDSM): Large collection with normal and abnormal findings and ground truth.
• Digital Retinal Images for Vessel Extraction (DRIVE): Digital images and expert segmentations of retinal vessels.
• Japanese Society of Radiological Technology (JSRT) Database: Digital Chest X-ray images with lung nodule locations, ground truth, and controls.
• Segmentation in Chest Radiographs (SCR) database: Digital Chest X-ray images with segmentations of lung fields, heart, and clavicles.
• Public Lung Database to Address Drug Response: Well documented chest CT images.
• Mammographic Image Analysis Society (mini-MIAS) Database: Mammographic images and markup.
• Standard Diabetic Retinopathy Database (DIARETDB1): Digital retinal images for detecting and quantifying diabetic retinopathy.
• SpineWeb: SpineWeb is an online collaborative platform for everyone interested in research on spinal imaging and image analysis.
• OAinitiative - MR data of Hips, knees and other sites affected by OA
• MR pediatric repository  - MR brain
• Facebase - 3D photography 
• Synapse - NIH-funded datasets.   For example, from UNC see https://www.synapse.org/#!Synapse:syn4152456

Data for registration method development and evaluation:

• Retrospective Image Registration Experiment (RIRE)
• Standardized Evaluation Methodology for 2D-3D Registration

Simulated and phantom data available for public use:

• BrainWeb: Simulated brain MR database.

Data from CAD competitions, some is available for public use:

• Portal for over 100 grand challenges in medical imaging:
• www.grand-challenge.org
• CAUSE07: Segment the caudate nucleus from brain MRI.
• BIOCHANGE 2008 PILOT: Measure changes.
• MS lesion segmentation challenge 08 Segment brain lesions from MRI.
• Liver Tumor Segmentation 08 Segment liver lesions from contrast enhanced CT.
• EXACT09: Extract airways from CT data.
• ANODE09: Detect lung lesions from CT.
• VOLCANO09: Quantify changes in pulmonary nodules.
• Coronary Artery Algorithm Evaluation Framework: Extract coronary artery centerlines from CTA data.
• ROC-Retinopathy Online Challenge: Detect microaneurysms for diabetic retinopathy screening.