Search Technologies

Researchers at the National Institute on Drug Abuse (NIDA) seek licensing or co-development of a mobile health technology that monitors and predicts a user’s psychological status in order to deliver an automated intervention when needed.

Researchers at the National Institute of Health (NIH) and National Institute of Standards and Technology (NIST) seek licensing or co-development partners for a method to predict functions, identity, disease state, and health of stem cells using machine learning.

Hospital Picture Archiving and Communication Systems (PACS) contain vast amounts of underutilized informatics about disease conditions. As computer image processing and systems advance, PACS informatics may form the foundation for precision automated computer-aided diagnostics for a wide range of disease conditions. Development of such systems may improve diagnostic accuracy and better inform treatment, but creating systems and algorithms capable of “learning” to recognize and locate the image patterns of disease and associated labels is a difficult problem. Researchers at the National Institutes of Health Clinical Center (NIHCC) have developed a technology that applies deep learning to PACS images to produce a database where certain disease features are identified and spatially located. Researchers at the NIHCC seek licensing of the PACS.

The Eunice Kennedy Shriver National Institute for Child Health and Human Development (NICHD) seeks research and co-development partners or licensees for an invention that discloses the diagnosis of pathologies in tissue related to changes in cell size, cellularity, cell infiltration, and other abnormalities detected by bulk water diffusion changes.

Researchers at the National Institutes of Health Clinical Center (NIHCC) developed a technology that improves segmentation detail levels for anatomical structures in medical images through a new, deep learning approach. Difficult anatomical features, often segmented incorrectly with other image segmentation methods, are correctly segmented and identified using this novel technology.

Available for licensing is computer software for the automated generation of density maps of macromolecular structures from a series of 2D digital micrographs of frozen hydrated specimens collected using an electron microscope equipped with an ultra-cooled computerized stage.

Researchers at the National Institutes for Health Clinical Center (NIHCC) have developed computer-aided diagnostics (CAD) that may further improve the already superior capabilities of multiparametric magnetic resonance imaging (MRI) for detection and imaging of prostate cancer. This system produces an accurate probability map of potential cancerous lesions in multiparametric MRI images that is superior to other systems and may have multiple product applications.

Researchers at the National Institute on Drug Abuse (NIDA) seek licensing and/or co-development research collaborations to further develop, evaluate or commercialize the software, Mobile Personalized Assessment & Learning for Addiction Treatment and Behavioral Modification. NIDA researchers developed this software for use in treating substance use disorders (drugs, alcohol, smoking) that provides personalized feedback to users.

The Frederick National Laboratory for Cancer Research seeks parties interested in collaborative research to co-develop software for the automatic 3-D visualization of biological image volumes.