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Method and System of Building Hospital-Scale Medical Image Database

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.

Computer-Aided Diagnostic for Use in Multiparametric MRI for Prostate Cancer

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.

Convolutional Neural Networks for Organ Segmentation

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.

Convolutional Neural Networks for Organ Segmentation

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.

Clinical Imaging with Acoustic Wave or Photoacoustic Tomosynthesis

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.

Robotic Exoskeleton for Treatment of Crouch Gait in Children with Cerebral Palsy (CP)

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.

Transperineal Ultrasound-Guided Prostate Biopsy

The National Institutes of Health (NIH) Clinical Center (CC) seeks Cooperative Research and Development and/or license agreements for Transperineal Ultrasound-Guided Prostate Biopsy

Topical Sodium Nitrate Ointment for Sickle Cell Disease

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.