Background:
There are many instances where quick and easy interpretation of a medical images, such as an x-ray, CT scan, MRI or ultrasound is useful. In these instances, the digital transfer of medical images between systems, providers, or users is difficult and time consuming due to the lack of interoperability of software protocols between imaging and diagnostic systems.
Invention Description:
Dr. Rick Mammone and Dr. Christine Podilchuk, researchers at Rutgers University have developed new, quick, cost-effective, and accurate solution for transmitting and interpreting medical images. The solution supports the use of a mobile device to capture a copy of a displayed medical (e.g., via photo) and uses deep neural network models to identify and correct image distortions. Corrections, identified by the neural network, can be generated as instructions that can be applied manually via by users or be performed automatically. Once corrections are applied the adjusted image can be recaptured.
This technology can be implemented for standalone use in medical image display and diagnostic technology (software, device, other.)
In addition, the technology can be bundled with four other related technologies from Dr. Mammone and Dr. Podilchuk to create a complete system for interpreting medical images. The other technologies include:
Advantages:
Market Applications:
Intellectual Property & Development Status:
US Patent 10,311,570 and pending continuation application; Available for use with new or existing image display/diagnostic applications or within a complete system comprised of additional related technologies from the inventors. We are seeking licensing and/or industry partners.