This software utilizes AI technology to automatically identify plaques on the transverse and longitudinal sections of the carotid artery by ultrasound, and frame the location of the plaques, which can greatly reduce the missed diagnosis rate of doctors.

This software adopts a self-developed ultrasound image segmentation algorithm, using 20000 ultrasound data for model training.

This software utilizes AI technology to automatically determine the scanning location (transverse and longitudinal) of the carotid artery, and automatically measure the thickness of the intima media in the ultrasound image, saving doctors the process of reviewing the entire video and improving their diagnostic efficiency.

This software adopts a self-developed semantic segmentation model with elastic scaling UNET and custom network layer, and uses 50000 ultrasound data for model training.

This software is mainly used for cardiovascular and cerebrovascular ultrasound examination in physical examination centers, as well as health screening in counties and townships. According to the research data of The Lancet, the global population with carotid atherosclerosis will reach about 2 billion in 2020. Among them, there are approximately 270 million people in China, with carotid artery plaques accounting for approximately 200 million. Cardiovascular and cerebrovascular ultrasound examination, as one of the main items of physical examination, has a wide scope, a large number of people, and a high workload for doctors.

This software helps doctors to quickly complete the examination through automatic plaque recognition, intimal thickness measurement and other functions, assists in analyzing the risk possibility of carotid atherosclerosis, transient ischemic attack, reversible neurological dysfunction and other diseases, and helps prevent high-risk diseases such as ischemic stroke and arterial embolism.

Using ultrasound models: GE/Philips/Mindray/Domestic handheld ultrasound

Available computing units: mobile phone/NVIDIA Xavier/computer/Cloud

Available deployment platforms: Android/Windows/Linux

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