Infervision’s A.I.—Augmented CT Screening Solution (AI—CT) is applied in early lung cancer screening. With its high paralleling computing power, AI—CT can precisely grasp the core characteristics of lung cancer and efficiently detect suspicious lung cancer lesions in CT scans. AI—CT is a technology that facilitates early detection and early treatment of lung cancer. Through comparison with physicians, AI—CT proves to increase the efficiency of lung cancer screening. AI—CT is especially sensitive to hard-to-detect nodules such as semi-solid and ground glass nodules and hence enhances radiologists’ diagnosis accuracy.


Infervision’s A.I.--Augmented X-ray Screening Solution (AI—DR) can detect more than 20 different kinds of cardiothoracic lesions. It helps screening diseases during both regular physical examinations as well as in-patient and out-patient radiology studies. AI—DR is especially sensitive to lung nodules on X-ray scans. During several months of use at a collaborating hospital, AI—DR helped screen out a few lung cancer patients who were initially misdiagnosed by radiologists. X-ray is often thought as an outdated medical imaging method. However, AI—DR is a technology that revives the significance of X-ray in medical imaging diagnosis.


Deep Learning Research Platform AI—Scholar surveys deep learning models to provide robust and powerful GPU computation for medical data modeling. The platform can process over 100 high-resolution medical DICOM images in one second. AI—Scholar includes the most advanced medical imaging related deep learning models. Doctors can combine and tailor models to investigate their own research questions. AI—Scholar features user-friendly interface. Through several brief clicks, a doctor without exposure to any programming experience can train a deep learning model. From Infervision’s perspective, deep learning should become part of the methodological toolkit in medical research.