Radiology

Products and services of Imsight involve three advantageous fields of radiology, pathology and radiotherapy and two emerging fields of ophthalmology and dermatology. Its products are widely available in hospitals, independent image and inspection centers,

DR-Sight

Chest X-ray A.I. assisted diagnosis system

DR-Sight can identify up to 18 pulmonary lesions, such as tuberculosis, pneumothorax, pleural effusion, etc. It can help doctors to quickly screen for signs, identify location of lesions, and automatically generate structured reports. DR-Sight is widely used in medical institutions and hospitals.
Advantages
(1) Instant result on binary classification (positive vs. negative); (2) Quickly identify 18 common clinical lesions; (3) Triage and index cases according to urgency level; (4) Heatmap and polygon analysis; (5) Structured report generation; (6) Provide deployment solutions.
Issues
The high volume of X-ray taken every day creates a large backlog of images that needed to be analyzed. With limited resources and the daily workload for radiologist is heavy. This could increase the risk of misdiagnosis and some lesions may not be found in time to meet the clinical needs.
Features
(1) Detect lesions ;

(2) Localized disease region ;

(3) Generate a structured report .

Lung-Sight

CT Pulmonary nodule A.I. diagnosis system

Lung-Sight enables patient data management, automatically detects lesions, generates structured report with clinical management guidelines, provides information on nodule’s nature and features with follow up function. This greatly improves the speed and quality of doctor’s analysis.
Advantages
(1) Learn from hundreds of thousands of lung CT cases by deep learning;

(2) Quantitative analysis on nodule’s nature;

(3) Can detect nodule that is smaller than 3 mm;

(4) Detection rate over 85%.

Issues
Manual detection of pulmonary nodules in clinical radiology comes with a large workload and takes a long time. There could be chances of missed diagnosis and misdiagnosis.
Features
(1) Detect pulmonary nodules;

(2) Provide quantitative analysis;

(3) Follow-up function;

(4) Generate a structured report.

BoneAge-Sight

Bone Age X-Ray AI-Aided Diagnosis System

BoneAge-Sight can perform diagnosis on the X-ray film using A.I. The bone age can be detected in milliseconds and the result is accurate up to month. The report is automatically generated with fast speed and high accuracy. It can be widely used in medical, sports, judicial and other fields.
Advantages
(1) Flexible installation and deployment;

(2) Detection in <1 second;

(3) High accuracy, ±0.4 years old;

(4) Perfectly connect with third-party systems.

Issues
The traditional bone age diagnosis method is cumbersome, time-consuming, labor-intensive, and has poor consistency. It is difficult to meet the professional needs.
Features
(1) Automatic detection of bone age;

(2) Predict growth and development;

(3) Generate a structured report.

Rib-Sight

Rib Fracture AI Identification System

Rib-Sight can rapidly and reliably identify rib fractures on chest X-rays and CT. The rib fracture identification on X-ray and CT images can be combined with DR-Sight and Lung-Sight respectively to maximize the analytic value of X-ray and CT images.
Advantages
(1) Detection in seconds;

(2) The detection rate is as high as 95% with less than 2 false positives.

Issues
Rib fracture is hard to tell and easily missed in scenarios of high workload. It is also time-consuming and laborious to locate a rib fracture.
Features
(1) Identify and locate fracture ;

(2) Semi-automatic report generation.

Liver-Sight

Liver Cancer AI Screening System

Screening for liver cancer enables early diagnosis and possible in-time treatment decision. CT and MRI are commonly used to screen for liver cancer. Liver-Sight can detect liver lesions from medical images and locate the lesion areas. Each lesion is quantitatively and qualitatively analyzed, and report is generated according to LI-RADS guideline.
Advantages
(1) Improve early screening detection rate;

(2) Quantitative qualitative analysis based on LI-RADS standard;

(3) Classification using international standard;

(4) Standardize liver cancer diagnosis process.

Issues
In the early stage of primary liver cancer, there has no obvious symptoms while the disease progression develops rapidly. Therefore, the early screening of liver cancer plays a vital role in the clinical treatment of patients. At present, early screening detection rate can be missed up to 40%.
Features
(1)Detection of liver lesions ;

(2)Locating of liver lesions ;

(3)Quantitative and qualitative analysis on lesions as per LI-RADS criteria ;

(4)Automatic generation of diagnosis reports .

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