The National Institutes of Health - Clinical Center (NIH-CC) seeks to license and/or co-develop methods of reading chest x-rays using a deep learning models to detect a disease and describe its contents.
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.
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.
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.