In today’s era, it’s imperative to have a fast and accurate diagnosis of skin conditions, including skin cancer. However, the conventional tools used for these diagnostics are usually out of reach for the average person due to their costs and complexity. This results in late treatments, and sometimes loss of lives as well.
According to a report from Elegant Hoopoe, Google has filed for a patent that could revolutionize skin diagnostics forever. The patent shows a disruptive solution that aims to democratize skin health monitoring by using already existing technology in several consumer devices, such as smartphones.
Back in 2021, Google launched a trial of its “dermatology assist tool”, which is capable of spotting skin, hair, and nail conditions by examining the images uploaded by patients. The app even has a CE mark in Europe.
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Google Working On A Tool To Detect Skin Cancer
Google has been developing health diagnostic technology since then, and it’s likely we see a more accurate tool capable of democratizing skin health monitoring and saving numerous lives.
The patent also suggests that the company wants to improve the early detection and diagnosis of skin conditions, especially skin cancer, by leveraging advanced tech. Rather than using only images, the patent describes a method and system that makes use of 3D sonic sensors to gain volumetric data about skin lesions, which are then analyzed with the help of machine learning models to identify potential skin cancer conditions.
The diagnostic results, including confidence levers, are shown on the computing device for further clinical evaluation. The tech will reduce the load on conventional diagnostic tools for skin conditions, which are usually very bulky and expensive, and require training to operate.
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How Will Google’s New Tool Detect Skin Conditions
The system will use a smartphone to display diagnostic outputs. The system uses machine learning to identify skin cancer features depending on volumetric data from ultrasonic pulses.
Unlike surface imaging, the system analyzes the depth of skin lesions, which is important to differentiate between benign and malignant conditions. A 3D ultrasonic sensor located under the smartphone display captures detailed images of skin lesions by resolving depth information through back-reflected ultrasonic pulses.
The system uses ultrasonography to penetrate dermal layers, offering more accurate clinical data when compared to conventional surface images. The machine learning model is trained with the help of high-resolution sensor data and annotated features to build a dictionary of skin cancer characteristics, which will come in handy to diagnose new cases. Not just that, the system is also capable of authenticating users through fingerprint scanning using the same 3D ultrasonic sensor technology.