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VinDr | Solutions for medical data

 Genereret December 23 2025 19:16 PM

Gammel data? OPDATER !

Scoren er 49/100

SEO Indhold

Titel

VinDr | Solutions for medical data

Længde : 34

Perfekt, din titel indeholder mellem 10 og 70 bogstaver.

Beskrivelse

VinDr is a comprehensive solution for medical image analysis that integrates Artificial Intelligence (AI) into a Picture Archiving and Communication System (PACS) to assist radiologists in making fast and precise diagnoses

Længde : 222

Kan optimeres; din meta beskrivelse bør indeholde mellem 70 og 160 karakterer (med mellemrum). Brug dette gratis redskab til at regne længden ud.

Nøgleord

vindr,ai,medical imaging,artificial intelligence,pacs,deep learning,radiology,healthcare,vinbdi

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Og Meta Egenskaber

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Egenskab Indhold
locale en_GB
site_name VinDr
type website
title VinDr | Solutions for medical data
description VinDr is a comprehensive solution for medical image analysis that integrates Artificial Intelligence (AI) into a Picture Archiving and Communication System (PACS) to assist radiologists in making fast and precise diagnoses
url https://vindr.ai

Overskrifter

H1 H2 H3 H4 H5 H6
3 1 12 0 2 20
  • [H1] VinDr CAD
  • [H1] Research
  • [H1] Contact Us
  • [H2] News
  • [H3] VinDr-ChestXR
  • [H3] VinDr-SpineXR
  • [H3] VinDr-Mammo
  • [H3] VinDr-ChestCT
  • [H3] VinDr-LiverCT
  • [H3] VinDr-BrainCT
  • [H3] VinDr-BrainMR
  • [H3] VinDr Lab: Open-source data platform for medical AI
  • [H3] Vingroup: Ứng dụng AI-VinDr để giải bài toán y tế bền vững
  • [H3] Đọc phim cùng người máy
  • [H3] Quick Links
  • [H3] Contacts
  • [H5] Shaping the future of medical data analysis
  • [H5] Smart Health Center – VinBigData JSC
  • [H6] VinDr CAD is a platform for medical image analysis that consists of multiple Computer-Aided Diagnosis (CAD) tools to assist doctors in making fast and precise diagnoses. The platform can be seamlessly integrated into any Picture Archiving and Communication System (PACS) without breaking standard clinical workflows. Each CAD tool can automatically suggest diagnosis and localize a certain number of abnormalities based on appropriate DICOM images  in a real-time fashion. Focusing on some of the most common imaging modalities, VinDr CAD currently offers 7 following tools.
  • [H6] We are passionate about applying computer vision (CV), machine learning (ML) and deep learning (DL) models to build computed-aided detection (CADe) and computer aided diagnosis (CADx) systems from very large-scale clinical datasets of multiple imaging modalities (X-ray, CT, MRI, etc). Our research includes new methods and ML/DL models for radiologist-level understanding and interpretation from medical images. We aim to validate and publish our work on top-tier journals and conferences.
  • [H6] Learning from multiple expert annotators for enhancing anomaly detection in medical Image analysis
  • [H6] Slice-level Detection of Intracranial Hemorrhage on CT Using Deep Descriptors of Adjacent SlicesVinDr-CXR: An open dataset of chest X-rays with radiologist’s annotations
  • [H6] VinDr-CXR: An open dataset of chest X-rays with radiologist’s annotations
  • [H6] An Accurate and Explainable Deep Learning System Improves Interobserver Agreement in the Interpretation of Chest Radiograph
  • [H6] Deployment and validation of an AI system for detecting abnormal chest radiographs in clinical settings
  • [H6] VinDr-SpineXR: A deep learning framework for spinal lesions detection and classification from radiographs
  • [H6] Learning to Automatically Diagnose Multiple Diseases in Pediatric Chest Radiographs Using Deep Convolutional Neural Networks
  • [H6] DICOM Imaging Router: An Open Deep Learning Framework for Classification of Body Parts from DICOM X-ray Scans
  • [H6] VinDr-RibCXR: A Benchmark Dataset for Automatic Segmentation and Labeling of Individual Ribs on Chest X-rays
  • [H6] Enhancing MRI Brain Tumor Segmentation with an Additional Classification Network
  • [H6] VinDr-CXR: An open dataset of chest X-rays with radiologist’s annotations
  • [H6] Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy
  • [H6] Interpreting chest X-rays via CNNs that exploit disease dependencies and uncertainty labels
  • [H6] Interpreting chest X-rays via CNNs that exploit disease dependencies and uncertainty labels
  • [H6] Detection and segmentation of endoscopic artefacts and disease using deep architectures
  • [H6] A CNN-LSTM Architecture for Detection of Intracranial Hemorrhage on CT scans
  • [H6] Address: 9th floor, Century Tower, Times City, 458 Minh Khai, Hai Ba Trung, Ha Noi
  • [H6] Email: [email protected]

Billeder

Vi fandt 27 billeder på denne side.

8 alt tags mangler eller er tomme. Tilføj alternativ tekst til dine billeder for at gøre siden mere brugervenlig, og for at optimere din SEO i forhold til søgemaskinerne.

Text/HTML balance

Balance : 11%

Denne sides text til HTML fordeling er under 15 procent, dette betyder at din side mangler indhold!

Flash

Perfekt, ingen Flash objekter er blevet fundet på siden.

iFrame

Perfekt, der er ikke nogen iFrames på din side!

URL Omskrivning

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Underscores i links

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On-page links

Vi fandt et total af 30 links inkluderende 5 link(s) til filer

Anker Type Juice
Products Intern Sender Juice
VinDr PACS Intern Sender Juice
VinDr CAD Intern Sender Juice
VinDr Lab Intern Sender Juice
Datasets Intern Sender Juice
Research Intern Sender Juice
News Intern Sender Juice
Contact Intern Sender Juice
VinBigdata Ekstern Sender Juice
Request Demo Ekstern Sender Juice
[email protected] Intern Sender Juice
VinDr-Mammo: A large-scale benchmark dataset for computer-aided diagnosis in full-field digital mammography Ekstern Sender Juice
Slice-level Detection of Intracranial Hemorrhage on CT Using Deep Descriptors of Adjacent Slices Ekstern Sender Juice
VinDr-CXR: An open dataset of chest X-rays with radiologist’s annotations Ekstern Sender Juice
An Accurate and Explainable Deep Learning System Improves Interobserver Agreement in the Interpretation of Chest Radiograph Ekstern Sender Juice
A novel multi-view deep learning approach for BI-RADS and density assessment of mammograms Ekstern Sender Juice
Deployment and validation of an AI system for detecting abnormal chest radiographs in clinical settings Ekstern Sender Juice
Phase Recognition in Contrast-Enhanced CT Scans based on Deep Learning and Random Sampling Ekstern Sender Juice
VinDr-Mammo: A large-scale benchmark dataset for computer-aided diagnosis in full-field digital mammography Ekstern Sender Juice
VinDr-SpineXR: A deep learning framework for spinal lesions detection and classification from radiographs Ekstern Sender Juice
Enhancing MRI Brain Tumor Segmentation with an Additional Classification Network Ekstern Sender Juice
VinDr-CXR: An open dataset of chest X-rays with radiologist’s annotations Ekstern Sender Juice
Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy Ekstern Sender Juice
Interpreting chest X-rays via CNNs that exploit disease dependencies and uncertainty labels Ekstern Sender Juice
Interpreting chest X-rays via CNNs that exploit disease dependencies and uncertainty labels Ekstern Sender Juice
admin Intern Sender Juice
VinDr Lab: Open-source data platform for medical AI Intern Sender Juice
Vingroup: Ứng dụng AI-VinDr để giải bài toán y tế bền vững Intern Sender Juice
Đọc phim cùng người máy Intern Sender Juice
Products Intern Sender Juice

SEO Nøgleord

Nøgleords cloud

pham system deep learning chest nguyen cad from hieu dataset

Nøgleords balance

Nøgleord Indhold Titel Nøgleord Beskrivelse Overskrifter
nguyen 57
hieu 28
chest 17
pham 16
learning 15

Brugervenlighed

Link

Domæne : vindr.ai

Længde : 8

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Fejl : 0

Advarsler : 0

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