Medical Image Post-processing Software (uOmnispace.CT)

by Shanghai United Imaging Healthcare Co.  · Based in China → — Advanced Medical Image Post-processing Software
Cardiology Nuclear Medicine Radiology

Contact for pricing
Regulatory Status Disclosed

Overview

uOmnispace.CT is a comprehensive medical image post-processing software developed by Shanghai United Imaging Healthcare Co., Ltd. It is designed for medical professionals, including physicians and trained medical technicians, to view, manipulate, evaluate, and analyze medical images. The software supports DICOM images and is compatible with various imaging modalities such as CT, MRI, and PET. It can function as a standalone device or integrate with other cleared software options. Key functionalities include 2D and 3D viewing, annotation, measurement tools, and both manual and automatic segmentation, enhanced by machine learning technology for features like rib extraction. The system is a software-only medical device, operable on standard off-the-shelf PCs, and allows multiple users to remotely access clinical applications on a network. It communicates with various imaging and hospital information systems via the DICOM3.0 standard. uOmnispace.CT is not intended to display digital mammography images for diagnosis in the U.S.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • 2D and 3D image viewing
  • Annotation and measurement tools
  • Manual and automatic segmentation (including AI-based rib extraction)
  • Comprehensive film and reports features
  • DICOM image support (CT, MRI, PET, SPECT)
  • Image registration and lesion segmentation
  • Quantitative analysis
  • Fusion imaging
  • Cardiac function analysis
  • Vessel analysis and TAVR planning

Use Cases

  • General medical image post-processing and analysis
  • Oncology workflow support (lesion segmentation, follow-up analysis)
  • Neurology (brain perfusion, brain scan quantification)
  • Cardiology (heart segmentation, coronary artery extraction, calcium scoring, TAVR planning)
  • Emergency diagnostics (rapid CT image evaluation)
  • Interventional procedure planning and guidance

What Physicians Need to Know

DICOM Support & Standards
Supports DICOM 3.0 standard for image processing, viewing, manipulation, communication, and storage of medical images. Allows import and export of DICOM formatted images and objects from/to network nodes, local/network drives, and optical media.
PACS Integration Method
Communicates with imaging systems and hospital information systems using the DICOM 3.0 standard. It can be used as a standalone device or integrated with other cleared software options and can be configured within a network to send and receive DICOM data. Supports multi-user remote access.
Reading Room Workflow Impact
Designed to enhance efficiency in image analysis and reporting through 2D/3D viewing, annotation, measurement, and both manual and AI-driven automatic segmentation tools. It includes features for film and report generation, aiming to aid timely and accurate diagnoses.
AI Model Architecture
Utilizes deep learning-based algorithms for various tasks, including rib and spine labeling, segmentation, and quantitative analysis of multiple organs and pathologies. Specific AI-driven analysis tools include lung nodule detection, brain perfusion analysis, and cardiovascular/liver evaluations.
FDA Clearance Pathway
Received FDA 510(k) clearance (K233209) on May 17, 2024, as a Class II medical device under product code QIH (Medical image management and processing system). The broader uOmnispace platform (K230039) and uOmnispace.MI (K233176) also have 510(k) clearances.
Supported Modalities
Primarily focused on CT images, uOmnispace.CT is part of the broader uOmnispace platform which supports multimodality images including CT, MRI, PET, and DR. It is not intended for displaying digital mammography images for diagnosis in the U.S.
Sensitivity & Specificity Data
Performance testing for ML-based rib segmentation on chest CT data showed an average Dice coefficient of 0.855 (exceeding 0.8 acceptance criteria). Deep learning-based spine labeling achieved an average identification rate greater than 92% for spine and 91.7% for rib labeling. Overall performance testing demonstrated high accuracy and generalizability comparable to predicate devices.
RSNA/ACR Validation
United Imaging Intelligence showcased work-in-progress AI at RSNA 2023, including a deep learning model for automated chronic total occlusion (CTO) with effectiveness verified by affiliated hospitals and results published in Radiology. This indicates a commitment to scientific validation and presentation at key industry events.
Physician Tip

Leverage uOmnispace.CT's AI-driven segmentation and quantitative analysis tools for enhanced efficiency in complex CT evaluations, particularly for lung nodules, brain perfusion, and cardiovascular assessments. The multi-user remote access and DICOM 3.0 compatibility facilitate seamless integration into existing radiology workflows, supporting collaborative diagnostics. While the software offers robust post-processing, always correlate AI findings with clinical context and patient history for comprehensive diagnostic accuracy. Note that it is not cleared for digital mammography diagnosis.

uOmnispace.CT is designed for broad interoperability, supporting the DICOM 3.0 standard for communication with various imaging modalities and hospital information systems (PACS). Its ability to function standalone or integrate with other cleared software options provides flexibility for deployment within diverse IT infrastructures. Ensure network configurations are optimized for DICOM data transfer to maximize the benefits of its remote access and processing capabilities.

Details

Category Radiology & Imaging AI
Pricing Contact for pricing
DeploymentOn-premise (software-only, runs on standard PCs); Networked access for multiple users; Stand-alone or integrated with other cleared software; SaaS and Hybrid models also mentioned for uOmnispace platform.
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status 1 AI-estimated

uOmnispace.CT (Medical Image Post-processing Software) received FDA 510(k) clearance under K242624. The 510(k) summary for this device was prepared on May 16, 2024.

Integrations
EHR Not specified
Specialties Cardiology, Nuclear Medicine, Radiology

What the Web Says

uOmnispace.CT is an advanced medical image post-processing software developed by Shanghai United Imaging Healthcare. It is designed for physicians and trained medical technicians to view, manipulate, evaluate, and analyze various medical images, including CT, MRI, and PET scans. The software offers comprehensive 2D/3D viewing, annotation, and AI-enhanced segmentation tools, supporting detailed analysis and reporting across specialties like oncology, neurology, and cardiology.

Overall: Positive

Strengths

  • Advanced 2D/3D viewing and annotation capabilities.
  • AI-enhanced segmentation tools for various organs and pathologies, including rib and spine labeling.
  • Multi-modality compatibility (CT, MRI, PET, SPECT, DR).
  • Supports quantitative analysis and multi-modality fusion for detailed reporting and clinical decision-making.
  • Flexible deployment options: on-premise, networked access, stand-alone, integrated, SaaS, and hybrid models.
  • FDA-cleared for various applications, including lung nodule analysis, colon analysis, dental applications, and cardiovascular combined analysis.

Limitations

  • No ratings or explicit user reviews found on platforms like G2, Capterra, or Reddit.
  • Specific claims about ease of use for advanced segmentation and analysis tools are less prominent compared to some competitors.
  • Not intended to display digital mammography images for diagnosis in the U.S.
  • While offering comprehensive post-processing, its primary focus appears to be on viewing and processing images for diagnosis rather than directly facilitating surgical intervention with physical models, unlike some specialized competitors.

Based on reviews from: Physician Ai Tools, Shanghai United Imaging Healthcare, X-ray Interpreter, HealthAidb u2014 Software, Innolitics

Last updated: 2026-07-19

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Press & Coverage

Innolitics
2025 Year in Review: Cardiology AI/ML SaMD 510(k) Clearances
This article reviews FDA 510(k) clearances for AI/ML SaMD in cardiology during 2025, noting that Shanghai United Imaging Healthcare Co., Ltd.'s Medical Image Post-processing Software (uOmnispace.CT) received clearance on May 14, 2025. The clearance is categorized under 'Plaque-related devices' and the product code QIH for Automated Radiological Image Processing Software.
2026-01
Innolitics
QIH u00b7 Automated Radiological Image Processing Software u2014 FDA Product Code
This page provides an overview of the FDA product code QIH for Automated Radiological Image Processing Software, listing recent cleared devices. It confirms that Shanghai United Imaging Healthcare Co., Ltd.'s Medical Image Post-processing Software (uOmnispace.CT) received a Traditional 510(k) clearance on May 14, 2025.
2026-05
Radiology AI Tools Directory
CT/CTA radiology AI tools | FDA-cleared directory
This directory lists FDA-cleared AI tools for CT/CTA radiology, including Shanghai United Imaging Healthcare Co., Ltd.'s Medical Image Post-processing Software (uOmnispace.CT). The software is categorized for image analysis/processing with a decision date of May 14, 2025.
2025-05
FDA
FDA 510(k) Applications Received During September, 2024
This FDA listing of 510(k) applications received during September 2024 includes an entry for Shanghai United Imaging Healthcare Co., Ltd.'s Medical Image Post-processing Software (uOmnispace.CT) with submission number K242624 on September 3, 2024.
2024-09
FDA
May 14, 2025 Shanghai United Imaging Healthcare Co., Ltd. Xin ...
This FDA document, dated May 14, 2025, confirms the clearance of Shanghai United Imaging Healthcare Co., Ltd.'s Medical Image Post-processing Software (uOmnispace.CT) under Trade/Device Name.
2025-05
Physician Ai Tools
uMR Omega with uWS-MR-MRS - Physician Ai Tools
This product listing mentions Medical Image Post-processing Software (uOmnispace.CT) from Shanghai United Imaging Healthcare Co., Ltd. in conjunction with the uMR Omega and uWS-MR-MRS systems.
2026-04

Videos

Product demos, reviews, and walkthroughs for Medical Image Post-processing Software (uOmnispace.CT).

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Frequently Asked Questions

uOmnispace.CT leverages AI algorithms to automate image analysis, reduce noise and artifacts, and highlight critical findings, thereby improving diagnostic accuracy and efficiency. This allows physicians to interpret images faster, detect subtle anomalies that might be missed by the human eye, and prioritize urgent cases, ultimately streamlining the diagnostic workflow.
As an AI-powered medical imaging software, uOmnispace.CT would typically hold regulatory clearances such as FDA 510(k) and CE Mark under the EU Medical Device Regulation (MDR), confirming its compliance with safety and performance standards. To ensure patient data privacy and security, the software adheres to strict regulations like HIPAA, often incorporating secure cloud platforms, data anonymization, and robust Quality Management Systems (QMS) like ISO 13485:2016.
uOmnispace.CT aims to differentiate itself through its specific AI algorithms, range of pathologies detected, and seamless integration with existing PACS/RIS systems. While many AI solutions offer automated analysis and improved accuracy, key comparisons would focus on its reported diagnostic accuracy (which can exceed 95% in specific areas), workflow efficiency gains, and the breadth of its AI-powered features across various imaging modalities.
The pricing structure for uOmnispace.CT typically follows common healthcare AI models, such as subscription-based, per-scan (fee-per-study), or enterprise licensing. Costs can vary significantly based on the imaging modality, the complexity of the AI features utilized, and the volume of studies processed. Many vendors offer flexible licensing options, including tiered pricing or customized plans to accommodate different institutional sizes and specific clinical needs.
Known limitations of AI algorithms in medical imaging include potential biases from unrepresentative training data, lack of generalizability across diverse patient populations, and the 'black-box' nature of deep learning, which can make it difficult to understand the AI's reasoning. Physician oversight is crucial; clinicians must critically evaluate AI outputs, especially in ambiguous cases, and maintain responsibility for final diagnostic decisions, supported by continuous system validation.
While uOmnispace.CT offers advanced AI capabilities, the extent of customization or fine-tuning for specific clinical protocols or unique patient populations can vary. Developing highly tailored AI solutions often requires significant investment in data engineering, MLOps, and validation to ensure accuracy and regulatory compliance. However, some systems may offer configurable parameters or integration capabilities to adapt to certain workflows.

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Suggest an Edit → | Last Verified: 2026-04-19 | First Added: 2026-04-19
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