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Description
DWV, or DICOM Web Viewer, is an efficient and open-source tool for viewing DICOM images, developed using JavaScript and HTML5, which operates seamlessly within contemporary web browsers, eliminating the need for any extra plugins or installations. This viewer empowers users to engage with DICOM medical images through widely used web technologies, featuring capabilities such as adjusting window/level settings, zooming in and out, panning across images, and measuring distances and angles, along with inspecting DICOM tags. Additionally, DWV accommodates various image layouts and supports both multi-frame and multi-series DICOM files, ensuring comprehensive functionality. Users can annotate images with basic tools and can easily load files from local storage or via URLs, enhancing usability. The viewer's drag-and-drop feature allows for convenient file management, and its flexible architecture enables developers to embed it into tailored web applications. Actively maintained on GitHub, DWV prioritizes responsive design, ensuring optimal accessibility across a range of devices including desktops, tablets, and smartphones, making it a versatile solution for medical imaging needs. Moreover, the viewer's ongoing updates and community support contribute to its robustness and reliability in handling medical image data.
Description
Fovia Ai's F.A.S.T. aiCockpit serves as an AI viewer that enhances navigation, visualization, and interaction with AI-generated results from various vendors and algorithms through a unified user experience that minimizes the number of clicks needed. This platform facilitates the visualization and interaction of all algorithm outcomes within a single, user-friendly interface, significantly improving the workflow for radiologists and clinical professionals. By providing physician-validated insights to AI orchestrators, PACS, and reporting systems, it adheres to the most up-to-date interoperability standards. The system is compatible with multiple AI formats, such as DICOM Structured Reports, DICOM Key Images, DICOM GSPS, and DICOM segmentation objects. Furthermore, F.A.S.T. aiCockpit boasts a cloud-ready architecture, enabling access to AI-assisted radiology results from anywhere at any time via any web-enabled browser. With just one straightforward integration, users can seamlessly complete their AI capabilities without the need to switch between various viewers, thus streamlining their overall workflow even further. This innovative approach not only enhances efficiency but also empowers healthcare professionals to make more informed decisions quickly.
API Access
Has API
No
API Access
Has API
No
Integrations
GitHub
No
HTML
No
JavaScript
No
OsiriX
No
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
DWV
Country
United States
Website
ivmartel.github.io/dwv/
Vendor Details
Company Name
Fovia Ai
Founded
2003
Country
United States
Website
fovia.ai/index.php/fast-aicockpit/
