GBT Researching Development of Radio Based Computer Vision System for Cardiovascular Applications
February 11, 2021 | Business WireEstimated reading time: 4 minutes

GBT Technologies Inc. is researching the potential development of a radio based computer vision system to be guided by AI for cardiovascular applications. This is the first phase of the research to evaluate an autonomous arterial clog cleaning mini-probe. A typical computer vision system has the ability to recognize objects via a camera’s imaging which is combined with a computer vision algorithm to process and interpret the image’s data. GBT is researching to the potential design of a new approach vision system, which would be radio based. When a transmitted electromagnetic wave (radio wave) encounters a change in medium, some or all of it may propagate into the new medium and the remainder is reflected.
The part that enters the new medium is called the transmitted wave and the other the reflected wave. The probe will include an on-board radio transmits and receive (transceiver) system. The design contemplates the probe transmitting and receiving radio waves and a neural network program used to analyze this data to construct a 3D image of the probe’s environment as it moves within arteries. The research is considering an AI system that will detect and identify clogs within arteries, alerting and proposing removal methods. The expected advantage of using radio waves is the capability to penetrate through blood medium, which has poor visibility for a camera-based computer vision system. In addition, it is envisioned that the radio vision will enable to “see” through clogging plaque, measuring its length, width, and type. When cleaning an arterial plaque, it is crucial to clearly identify the artery’s wall and harming plaque to avoid damage to the artery walls, making a clear distinction for safe clogs removal.
The research is aiming to use of an intravenous mini-capsule unit that could autonomously travel within an artery, searching for clogs including total occlusions. In addition, radio waves technology will be evaluated to perform a “look-ahead” function that can be of a major assistance in curled arteries cases which are major challenge in the cardiovascular domain. It is expected that an AI based program will perform the necessary calculation to produce a clear image of the clog and its nature. The research will then evaluate whether this information will be used for the further cleaning stage which the system will be carefully removing the clog. In case of a total occlusion, it is envisioned that a clog-drilling option will be evaluated to insert a coronary stent, which is a tube-shaped device placed in the coronary arteries that enables supply blood, keeping the arteries open in the treatment of coronary disease. The system is aimed to offer a capability to be manually remote controlled by physicians or to autonomously operated inside blood vessels. It is intended that an advanced, miniature circuitry with an embedded software will control the unit's operations. The first phase of the research will be focused on a radio-based computer vision system in order to define one of the most important system’s features which is the capsule navigation through blood medium, clogs identification and its distinct, safe removal. We believe that such system can replace invasive procedures like angiogram, catheterization, and heart-bypass surgery.
There is no guarantee that the Company will be successful in researching, developing or implementing this system. In order to successfully implement this system, the Company will need to raise adequate capital to support its research and, if successfully researched, developed and granted regulatory approval, the Company would need to enter into a strategic relationship with a third party that has experience in manufacturing, selling and distributing this product. There is no guarantee that the Company will be successful in any or all of these critical steps.
We start with probably what is the most important feature of this research, which is the computer vision system. Machine vision has come of age for the past decades enabling wide variety of advanced applications in various domains. Typically, a machine vision system uses a camera to view an image, and a computer vision algorithm to process and interpret the image’s data. Inside a human’s artery there is no sufficient visibility for such a system due to the blood medium composition, and therefore a different approach is being considered; a radio-based vision system. Radio waves have the capability to pass through materials, and reflecting back waves data. Using this type of technology, we will be evaluating whether it can be used to determine the construction of an inner artery imaging, including clogs and their information. We believe electromagnetic waves can pass through the blood, identify organs like heart’s valves, artery vessel walls, and clogs. Using radio technology, we are researching whether the system will be able construct a complete image of the inner artery, as the miniature probe is moving within the blood vessel. One of the main advantages of such a system is its capability to identify total occlusion and measure its length inside the artery.
Furthermore, this type of “Look-Ahead” system can accurately identify and measure such a clog even in curled arteries which is typically a major challenge in the cardiovascular domain. The image is expected to be shown on an external computer monitor for a physician review before taking any action. The research will evaluate artery’s cleaning options upon clogs detection in future research phase. The radio system will enable an efficient navigation within arteries, avoiding damaging artery’s walls, identifying clogs, providing clog’s size, length, and shape. Using an AI program, a comprehensive, 3D views of capsule’s surroundings will be provided on a computer monitor while traveling inside the artery. The radio-based vision system is aimed to cover a wide range of situations where visible-medium imaging fails, enabling clear imaging in real time. We strongly believe that such a system, if fully developed, can have a huge potential for further health related applications, inside and outside a human body, to provide preventative medicine and replace invasive medical procedures and surgeries.
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