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What is Mango Viewer?

Mango Viewer is a powerful graphical user interface designed specifically for the analysis of medical images, accommodating a wide range of file formats, including DICOM, NIfTI, and ANALYZE. This application provides an extensive array of tools for examining and interpreting medical imaging data, featuring multi-planar viewing options such as axial, sagittal, and coronal views, in addition to sophisticated surface rendering capabilities and functions for defining and analyzing regions of interest. The user-friendly interface of Mango facilitates scripting and batch processing, making repetitive tasks much easier for users. Moreover, it includes advanced features like image overlay, image fusion, and visualization of 4D data, along with dynamic contrast-enhanced imaging capabilities. Users can leverage ROI tools to extract important statistical information, such as volume, mean, and standard deviation, and they can create ROIs either manually or through automated methods. Furthermore, Mango’s proficiency in managing multiple images proves beneficial for comparative studies, and its functionality is enhanced by plugins that cater to brain mapping, tractography, and perfusion analysis. Notably, this adaptable software is platform-independent, ensuring users can access it across various systems. With its rich set of features and capabilities, Mango Viewer serves as an invaluable resource for researchers and professionals within the medical imaging domain, facilitating innovative studies and advancements in the field.

What is F.A.S.T. aiCockpit?

Fovia Ai's F.A.S.T. aiCockpit functions as an advanced AI viewer that improves the ease of navigation, visualization, and interaction with results generated by AI from different vendors and algorithms, all through a streamlined user experience that reduces the number of clicks required. This platform allows for the comprehensive visualization and engagement with algorithmic outcomes, presented in a single, intuitive interface that greatly benefits the workflow of radiologists and clinical specialists. By offering physician-validated insights to AI orchestrators, PACS, and reporting systems, it meets the latest interoperability standards in the industry. The system supports a variety of AI formats, including DICOM Structured Reports, DICOM Key Images, DICOM GSPS, and DICOM segmentation objects. Additionally, F.A.S.T. aiCockpit features a cloud-compatible architecture, which provides the ability to access AI-assisted radiology results from any location at any time using any web-enabled browser. With a single, simple integration, users can effortlessly enhance their AI capabilities without toggling between different viewers, thereby further optimizing their overall workflow. This forward-thinking solution not only boosts efficiency but also equips healthcare professionals to make quicker, more informed decisions, ultimately leading to improved patient care and outcomes. As a result, the integration of such advanced technology into medical practices signifies a transformative step for the future of healthcare.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Mango Viewer

Date Founded

2006

Company Location

United States

Company Website

mangoviewer.com/mango.html

Company Facts

Organization Name

Fovia Ai

Date Founded

2003

Company Location

United States

Company Website

fovia.ai/index.php/fast-aicockpit/

Categories and Features

Categories and Features

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