U.S. Food and Drug Administration

This regulatory science tool (RST) describes a method to characterize digital image quality on optical see-through augmented reality head-mounted displays (AR HMDs) in ambient lighting conditions. The method can be implemented to measure AR display performance, such as Michelson contrast and contrast uniformity.

This regulatory science tool is a lab method that may be helpful while evaluating high intensity therapeutic ultrasound (HITU) devices.

This regulatory science tool comprises a model for conducting a retrospective analysis of COVID-19 intervention strategies.

This regulatory science tool is a method and phantom design for the evaluation of iodine-specific quantitative measurements, specifically the accurate estimation of iodine concentration within contrast-enhanced spectral CT.

This regulatory science tool is a synthetic mammography dataset that includes a variety of breast densities, breast sizes, and inserted lesions imaged with different exposure levels. The dataset is intended to be used for the comparative evaluation of AI tools used in mammography.

This regulatory science tool (RST) is a lab method for evaluating the safety of critical time-dependent radiant power, spectral, and temporal characteristics for multiwavelength high-power laser pointers and handheld compact laser products

This regulatory science tool is a lab method for performing platelet and leukocyte count assays per the <a href="https://www.iso.org/standard/63448.html">ASTM F2888-19 standard</a>, as a part of in vitro thrombogenicity assessment of blood-contacting medical device materials.

This regulatory science tool (RST) is a method for assessing the image quality of a head mounted display using the display’s transverse chromatic aberration characteristics to align the light measuring device to the eye-point/ center of the eye-box.

This regulatory science tool is a software program written in Python for analyzing whole slide images (WSIs) and assisting developers or pathologists in the assessment of machine learning algorithms used in digital pathology.

This regulatory science tool is a lab method for building a 5G network testbed to assess data transmission of medical device functions using 5G connectivity.