VinDr
COMPREHENSIVE AI SOLUTION FOR MEDICAL IMAGING
Comprehensive solution for medical imaging that integrates Artificial Intelligence (AI) into a Picture Archiving and Communication System (PACS) to assist radiologists in making fast and precise diagnoses. It aims to be an AI-assisted tool for doctors, which helps to improve the patient care and public health.
AI diagnostic features
Correct localizing lesions
Studies management and viewer
Outstanding Advantages
lesions
Mean accuracy of over 90% with VinDr-ChestXR and over 85% with VinDr-Mammo
health systems
Work independently or be two-way integrated with HIS/RIS/EMR/PACS/...
at the same time
Support multi-site diagnosis, perform analyzing multiple studies at the same time, across multiple devices
deployment
Flexible deployment, able to expand or scale down easily with cloud computing technology
Ministry of Health
Meet the HL7 FHIR standard for information exchange between information technology systems according to the standard of the Ministry of Health
Highlighted Features
PACS is the Picture Archiving and Communication System
- Manage studies in DICOM format (X-RAY, CT, MRI)
- Easily integrated with scanners or PACS
- DICOM viewer for radiologists
- Support radiologists to modify and approve diagnostic results as well as generate medical reports
Support medical imaging analysis and processing
- Provide both disease labels as well as bounding box annotations for localizing lesions
- Automatically diagnose multiple studies in real-time
- Modules available: VinDr-ChestXR, VinDr-Mammo, VinDr-SpineXR, VinDr-LiverCT and VinDr-ChestCT
- Upcoming modules: VinDr-BrainMR and VinDr-BrainCT
Tài liệu hướng dẫn
Phản hồi của khách hàng
Chính sách giá
*Báo giá trên chưa bao gồm: Thuế và các loại phí liên quan và phát triển các tính năng riêng cho doanh nghiệp
Research Achievements
CheXpert competition organized by Stanford University, 2019
Abnormal Image Detection in Endoscopy Videos (EndoCV), 2020
Pulmonary Embolism Detection Challenge, organized by the Radiological, Society of North America (RSNA), 2020
