Medical AI

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Optimize clinical efficiency with AI-driven workflow

Accurately detect intracerebral hemorrhage (ICH) and identify five types of ICH in non-contrast computed tomography (CT) scan

Automatically delineate 17 types of head-and-neck organs-at-risk on CT images and assist radiation oncology professionals in expediting treatment planning workflow

Through artificial intelligence algorithms analyzing whole-body bone scintigraphy images, it assists nuclear medicine specialists in examining the distribution of hotspots. This aids in detecting potential bone metastases, while also highlighting suspected areas for reference by clinical physicians

Automatically delineate 80 critical organ structures on computed tomography (CT) images, including regions such as the head, neck, and pelvic lymph nodes. Highly compatible, it works with any brand of treatment planning system available in the market, ensuring seamless integration with various CT and TPS systems

Atrial Premature Beat 心房早期收縮

Applicable for outpatient and emergency department. Able to analyze rhythm interpretation results automatically from 12-lead electrocardiograms and output the results to assist clinical physicians in quickly identifying heart anomaly and providing appropriate treatment.

Analyze 12-lead electrocardiograms to assist healthcare professionals in quickly detecting acute myocardial infarction, in order to increase the chance of early treatment for patients with acute myocardial infarction

Automatically measure the maximal transverse diameter of heart and maximal inner transverse diameter of thoracic cavity further to calculate the cardiothoracic ratio of a chest X-ray image. Enable outputting structured reports, optimizing report generation efficiency, and assisting different types of physicians in focusing more on clinical decision-making and patient care.

Provide nuclear radiologists a complete review and quickly modify of paitent's report to shorten the time for diagnostic and clinical decision making.

Identify 15 abnormal finding in chest X-ray images with heart, lungs and bones. The system as a pre-read assistance enable a quick interpretation and faster decisions

Evaluate left hand X-ray images of children and adolescents at age 2 to 16 years to assess bone age. Assist pediatricians or clinicians distinguish if a child's bone development is normal, delayed, or advanced for diagnosis and treatment

A system for managing digital images and communications in medicine. Assists in displaying, processing, storing, and transferring data in compliance with DICOM images. Enable filtering, digital manipulation and quantatitve measurements as well.

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