ProtonPACS Reviews & Ratings

ProtonPACS

4.8 out of 5 stars

Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

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Ratings and Reviews 5 Ratings

Total 5 out of 5 stars
ease 5 out of 5 stars
features 5 out of 5 stars
design 4 out of 5 stars
support 5 out of 5 stars

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What is Syngo Carbon?

Syngo Carbon is an enterprise imaging and knowledge platform built to support modern, patient-centered healthcare delivery. Developed with decades of Siemens Healthineers expertise, it integrates PACS, VNA, digital pathology, niche applications, and encounter-based imaging into one unified environment. The solution provides a single source of truth for imaging and clinical data, ensuring clinicians can view a patient’s full health profile across the entire care journey. AI-powered workflows, actionable reporting, and premier visualization tools help transform complex data into meaningful insights. Syngo Carbon’s flexible, modular design allows organizations to adapt, scale, and innovate as clinical and operational demands change. Its clean, intuitive reading and reporting workspace simplifies collaboration across departments. Together, these capabilities help healthcare providers improve efficiency, decision accuracy, and patient outcomes.

What is ProtonPACS?

ProtonPACS is a comprehensive picture archiving system that excels in managing the storage and distribution of images while streamlining workflows across healthcare organizations. This solution features both front-end and back-end patient management systems designed to minimize the need for manual data entry or the risk of duplicating patient information. It supports seamless integration with HL7 protocols to connect with various information systems, including electronic health records (EHRs) and radiology information systems (RIS). Moreover, ProtonPACS incorporates Intelerad's Inteleviewer, a powerful diagnostic tool that enables radiologists and healthcare professionals to enhance images, adjust layouts, take precise measurements, carry out image reconstructions, and generate important visual summaries. Utilizing an integrated speech recognition engine and worklist, radiologists can efficiently prepare reports for referring physicians. All reports and images can be accessed through the system's portal on any device with web capabilities, ensuring flexibility and convenience. Additionally, ProtonPACS employs a secure hybrid architecture that leverages both local hardware and cloud hosting to provide reliable and efficient service. This innovative combination enhances data security while ensuring accessibility and performance throughout the healthcare facility.

Media

Media

Integrations Supported

Fluency for Imaging

Integrations Supported

Fluency for Imaging
MedicsRIS

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

$2/study
Pricing starting at $2 per study or a minimum spend of $6k or more annually. Implementation fee starting at $5k.

Supported Platforms

SaaS

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Online Training
On-Site Training

Company Facts

Organization Name

Siemens

Date Founded

1847

Company Location

Germany

Company Website

www.siemens-healthineers.com/en-us/digital-health-solutions/syngo-carbon

Company Facts

Organization Name

Radsource

Date Founded

1999

Company Location

United States

Company Website

radsource.us

Categories and Features

Medical Imaging

Not specified

PACS

Image Management
Mobile Access

Categories and Features

Medical Imaging

Not specified

PACS

Comparison View
Data Compression
Diagnostic Reporting
HL7 Support
Image Management
Mobile Access
Referring Physician Portal
Voice Recognition

Radiology

Audit Trail
EMR HL7 Bridge
Image Fusion
PACS Integration
Scanning Input

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