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Innovative Use of Mobile Devices for Medical Image Capture and Diagnostics

Invention Summary:

There are many instances where quick and easy interpretation of a medical images, such as an x-ray, CT Scan, MRI or ultrasound is needed; for example, in a fast-paced trauma unit, or during a regional disaster or mass casualty incident. In these instances, the digital transfer of medical images, as wells as diagnosis, is difficult and time consuming due to the lack of interoperability of software protocols between imaging and diagnostic systems.

Researchers at Rutgers University have developed a new, quick, cost-effective and accurate solution for transmitting and interpreting medical images. The technology captures an image (e.g. user takes a photo via smart phone or other camera) of a displayed medical image. The captured image is processed locally on the device or is transferred for subsequent processing.

The Rutgers solution can correct image artifacts from the photographic process and provide image interpretation for human experts (e.g., a telemedicine, teleradiology setting) or by artificial intelligence or other types of software applications.

Other features of the technology include:

the ability to locate suspicious lesions in an image with high probability of malignancy or other disease states using a single-image method to find the regions of interest in real-time.
a heat map for visualizing regions of interest that explains a decision made by the (AI) software (e.g., shows pixels salient in the decision process)example such as highlighting a spiculated edge of a breast lesion to indicate that it is suspicious

Advantages:

Fast, low cost & interoperable for transfer of medical images with different formats from different systems
Improves the quality of captured medical images using mobile devices
Includes diagnostic features for identifying medical areas of concern
Provides an open interchange where AI-based medical diagnostic tools can be used by healthcare providers from their mobile device, that support use of enhanced deep learning models as they become available from various vendors.