Search Technologies

Ultrasound-based cancer screening and biopsy imaging technique are a critical clinical need. Ultrasound based biopsy imaging can provide a real-time modality for lower cost that is comparable to, or complimentary to MRI imaging. Researchers at the NIH Clinical Center seek licensing and/or co-development research collaborations for Tissue Characterization with Acoustic Wave Tomosynthesis.

Computer automated segmentation of high variability organs and disease features in medical images is uniquely difficult. The application of deep learning and specialized neural networks may allow for automation of such interpretation tasks that are currently only performed by trained physicians. Computer automation may improve image analysis capabilities and lead to better diagnostics, disease monitoring, and surgical planning for many diseases. To help solve this challenge, researchers at the National Institutes of Health Clinical Center (NIHCC) have developed a technology that trains a computer to read and segment certain highly variable image features.

The National Institute of Health - Clinical Center (NIH-CC) seeks licensing and/or co-development of a system and method for tracking eye movement to increase the efficacy of visual diagnoses by radiologists.

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.

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, which is available for licensing or co-development.

Researchers at the National Institutes of Health Clinical Center (NIHCC) and Northern Arizona University (NAU) seek licensing and/or co-development research collaborations for a wearable, pediatric, robotic exoskeleton that facilitates knee extension during walking to provide motorized movement assistance and training through the gait cycle. The Robotic Exoskeleton is specifically designed for therapy of crouch gait in children with cerebral palsy (CP). The design is a customizable human-machine interface that allows an individualized assistance protocol to help preserve and enhance muscle strength and control. Early clinical results from this intervention appear promising for a condition having few effective long-term interventions.

The National Institutes of Health, through The National Institutes of Health - Clinical Center (NIH-CC) and the National Heart Lung and Blood Institute (NHLBI), seeks licensing and/or co-development partners for a nitric oxide cream for the treatment of ulcers associated with sickle cell disease.