Deep Recon

by Shanghai United Imaging Healthcare Co.  · Based in China → — Deliver a New Reality of AI Technology
Radiology
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Regulatory Status Disclosed

Overview

Deep Recon (also integrated as uAIFI DeepRecon) is an AI-powered, deep learning-based image reconstruction software developed by Shanghai United Imaging Healthcare Co. It is designed to process raw imaging data to enhance diagnostic image quality across both computed tomography (CT) and magnetic resonance imaging (MRI) modalities.

The tool is utilized by radiologists, imaging technologists, and clinical specialists across hospital departments, outpatient imaging centers, and oncology clinics. It supports a broad range of clinical applications, including head, chest, abdomen, cardiac, and vascular imaging.

Deep Recon integrates directly into the reconstruction chain of compatible United Imaging scanners (such as the uCT and uMR series). In clinical workflows, the software operates automatically during the acquisition phase. It utilizes deep neural networks to perform intelligent denoising and K-space-interpolation based image super-resolution. This allows clinical practices to achieve high-resolution anatomical details and improved signal-to-noise ratio (SNR) without requiring longer scan times.

  • Intelligent Denoising: Suppresses unwanted image noise while preserving sharp anatomical boundaries and low-contrast detectability.
  • Super-Resolution Reconstruction: Employs deep learning algorithms to interpolate data, enhancing spatial resolution and image sharpness.
  • Multi-Modality Compatibility: Available as a reconstruction solution for both advanced CT and MRI systems.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • Deep learning-based image reconstruction
  • Intelligent denoising for improved signal-to-noise ratio (SNR)
  • Increased image sharpness and resolution
  • Potential for reduced scan time
  • Part of uAIFI technology platform
  • High fidelity with double safety lock design (image and K-space domain)
  • Applicable for multi-bed scanning like whole spine and whole-body imaging
  • Enhances diagnostic accuracy and patient care

Use Cases

  • Enhancing diagnostic accuracy in MRI examinations
  • Improving patient comfort through faster and quieter scans
  • Optimizing workflow and throughput in imaging departments
  • Facilitating high-resolution imaging with ease
  • Supporting comprehensive advanced clinical applications

What Physicians Need to Know

DICOM Support & Standards
Deep Recon is an image reconstruction algorithm integrated into United Imaging's MRI and CT systems, which inherently support DICOM for image storage and transfer. FDA 510(k) clearances for systems incorporating Deep Recon imply adherence to relevant medical imaging standards, including DICOM. [7, 8, 10, 12, 15]
PACS Integration Method
As an integrated image reconstruction technology within United Imaging's MRI and CT systems, Deep Recon produces standard DICOM images that are then sent to PACS, implying a standard DICOM-based integration. [7, 8, 10, 15]
Reading Room Workflow Impact
Deep Recon enhances image quality by increasing sharpness and signal-to-noise ratio (SNR), and for CT, improves low contrast detectability and reduces image noise, potentially leading to increased diagnostic confidence and more efficient reading. It enables either improved image quality without prolonging imaging time or reduced imaging time without sacrificing image quality. [1, 2, 3, 4, 8, 10, 11]
AI Model Architecture (deep learning approach)
Deep Recon is a deep learning-based image reconstruction algorithm. For MRI, it utilizes a convolutional neural network (CNN) trained model for reconstruction, performing intelligent denoising and K-space interpolation for super-resolution. For CT, it employs dedicated deep neural networks trained for different body parts. [1, 2, 3, 4, 7, 8, 11]
Processing Speed (per study)
For MRI, Deep Recon, especially when combined with AI-Assisted Compressed Sensing (uAI ACS), can significantly reduce image construction time, with reported reductions of nearly 95%, potentially bringing reconstruction time to under one minute. [9]
FDA Clearance Pathway (510k/De Novo)
Deep Recon has received 510(k) clearance from the FDA. The CT version (K193073) was cleared in July 2020. The MRI version, as part of the uMR 680 system (K230403), was cleared in February 2023. An update for uCT 780 (DELTA (Deep Recon)) also received 510(k) clearance in January 2025. [7, 8, 10, 12]
Supported Modalities (CT/MRI/X-ray/US)
Deep Recon is supported on United Imaging's **MRI** systems (e.g., uMR 680, uMR OMEGA) and **CT** systems (e.g., uCT 760, uCT 780, uCT 550). [1, 2, 3, 4, 7, 8, 10, 11, 15, 19]
Sensitivity & Specificity Data
Specific sensitivity and specificity data for Deep Recon itself are not explicitly provided in the available information. However, the technology is designed to improve image quality, leading to enhanced diagnostic accuracy and confidence. [1, 2]
RSNA/ACR Validation
United Imaging consistently showcases its AI technologies, including Deep Recon, at major radiological conferences like RSNA, demonstrating its engagement with the scientific and clinical community. [3, 11, 13, 18, 20, 21]
Physician Tip

Deep Recon offers significant advantages for image interpretation by providing sharper anatomical details, reduced noise, and improved signal-to-noise ratio. For MRI, it can contribute to shorter scan times, enhancing patient comfort and throughput. For CT, it allows for lower radiation doses while maintaining or improving diagnostic image quality, particularly for low-contrast detectability. Physicians can expect increased diagnostic confidence due to the enhanced image clarity.

Deep Recon is seamlessly integrated as a core image reconstruction feature within United Imaging's compatible MRI and CT scanner platforms. It operates by processing raw imaging data to produce high-quality DICOM images, ensuring direct compatibility with existing PACS, viewing workstations, and reporting systems without requiring additional middleware or complex integration steps.

Details

Category Radiology & Imaging AI
Pricing Contact for pricing
DeploymentIntegrated into United Imaging's MRI systems (e.g., uMR 680, uMR OMEGA)
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status 1 AI-estimated

DeepRecon is a deep-learning based image processing algorithm for image de-noising and K-space-interpolation based image super-resolution, part of a 510(k) submission by Shanghai United Imaging Intelligence Co., Ltd. dated February 16, 2023. [cite: 13 (previous search)]
Integrations
EHR Not specified
Specialties Radiology

What the Web Says

Deep Recon, a deep learning-based image reconstruction algorithm by United Imaging, is designed to enhance MRI scanning by improving signal-to-noise ratio and image sharpness. It is part of the uAIFI technology suite found in their uMR 680 MRI system, which aims to provide high-resolution imaging, fast and quiet scans, and an optimized workflow for healthcare professionals. While there's general interest in deep learning MRI reconstruction technologies among radiologists, specific detailed reviews from physicians or healthcare IT professionals for Deep Recon are limited.

Overall: Positive

Strengths

  • High-resolution and high-signal deep learning reconstruction.
  • Intelligent denoising for improved signal-to-noise ratio.
  • Increased image sharpness.
  • Fast and quiet scan capabilities with the uMR 680 system.
  • Easy-to-use software and one-click workflow (EasyScan) for technologists.
  • Optimized workflow and comprehensive advanced clinical applications.

Limitations

  • Limited independent reviews from physicians and healthcare IT.
  • Potential concerns about data security with Chinese-manufactured equipment (general United Imaging concern, not specific to Deep Recon).
  • Some general negative sentiment regarding United Imaging's customer service and sales approach in broader discussions.

Based on reviews from: United-Imaging.com, Reddit, G2, Capterra

Last updated: 2026-07-18

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Press & Coverage

FDA
510(k) Premarket Notification for Deep Recon
The FDA cleared Deep Recon, a deep learning-based image reconstruction method for CT systems (uCT 760 and uCT 780) by United Imaging, in July 2020. It aims to reduce image noise, improve low contrast detectability, and potentially lower radiation dose for adult head, chest, abdomen, cardiac, and vascular CT applications.
2020-07
Chinese Journal of Hepatology
Research progress and prospects of the application of radiographic imaging in the precise diagnosis and treatment of hepatocellular carcinoma
This article mentions that United Imaging's Deep Recon low-dose imaging technology, based on uAI deep learning algorithms, received FDA approval in 2020. It highlights Deep Recon's ability to significantly reduce image noise and maintain good image quality and diagnostic performance in liver enhanced examinations, even with half the radiation dose, making it valuable for precise diagnosis and follow-up of hepatocellular carcinoma.
unknown
Physician Ai Tools
uMR Omega with uWS-MR-MRS - Physician Ai Tools
United Imaging Healthcare's Deep Recon is mentioned in the context of imaging technology news, indicating its role in radiology and imaging AI.
2026-04
Fora Spa
uAIFI TECHNOLOGY - Fora Spa
This article from Fora Spa, an Italian distributor, highlights uAIFI DeepRecon as a deep learning-based image reconstruction technology that improves image definition and signal-to-noise ratio for better visualization of anatomical details and diagnostic confidence. It notes that CE registration is in progress and it's not yet commercially available in the EU.
unknown
Crown Healthcare
uMR 670 - Crown Healthcare
Crown Healthcare introduces United Imaging's Deep Recon as a deep learning-based image reconstruction technology for intelligent image de-noising and K-space-interpolation based image super-resolution, providing '3T-like' imaging performance on a 1.5T wide-bore system.
unknown
Radiology AI
Deep Recon | Shanghai United Imaging Healthcare Co., Ltd
Deep Recon is listed as an FDA-cleared radiology AI product for CT/CTA by Shanghai United Imaging Healthcare Co., Ltd., with links to FDA source documents.
unknown
FDA
510(k) Premarket Notification for uCT 780 (DELTA (Deep Recon) feature modification)
An FDA regulatory announcement from January 2025 details a modification to the DELTA (Deep Recon) feature within United Imaging's uCT 780 system. The changes aim to reduce dose at the same resolution, increase low contrast resolution at the same dose, and substantially reduce noise without creating a new intended use.
2025-01
FDA
510(k) Premarket Notification for uCT 550 (DELTA (Deep Recon) algorithm optimization)
A January 2025 FDA announcement describes the optimization of the DELTA (Deep Recon) algorithm in United Imaging's uCT 550. This optimization enhances image quality with lower noise and improved low contrast detectability, and can reduce the required diagnostic CT imaging dose.
2025-01

Videos

Product demos, reviews, and walkthroughs for Deep Recon.

View all on YouTube

Frequently Asked Questions

Deep Recon, or Deep Learning Reconstruction, uses artificial intelligence to enhance medical images by reconstructing them from raw data, leading to sharper, clearer images with reduced noise and artifacts. This technology can significantly improve diagnostic confidence and potentially shorten scan times for modalities like MRI, CT, and PET/CT, enhancing patient experience and workflow efficiency.
Yes, leading Deep Learning Reconstruction technologies, such as GE HealthCare's AIR Recon DL, have received FDA 510(k) clearance, indicating they meet regulatory standards for clinical use. These systems have been evaluated on thousands of cases across various anatomies and patient demographics, demonstrating improved image quality and diagnostic utility.
While Deep Recon offers significant advantages, potential limitations include its reliance on extensive training data, which could introduce biases if the data isn't diverse enough. Clinicians also need to understand that while image quality is enhanced, the fundamental physics of image acquisition still apply, and careful parameter selection remains crucial.
Deep Recon often outperforms traditional reconstruction methods by building its own model from large datasets, leading to superior noise reduction, artifact suppression, and enhanced resolution without the historical trade-offs between scan time and image quality. Unlike some AI solutions focused on post-processing or interpretation, Deep Recon is integrated into the fundamental image formation process.
Deep Recon solutions are often available as software upgrades for existing imaging systems, potentially avoiding the significant financial investment of replacing entire machines. Integration is typically seamless, generating enhanced images in real-time at the operator's console, and can lead to improved operational efficiencies and patient throughput, which may offer long-term cost benefits.
Deep Recon systems typically process de-identified raw imaging data, and the AI models are trained on large, anonymized datasets to protect patient privacy. Vendors adhere to strict healthcare data security protocols and compliance standards, ensuring that sensitive patient information is not compromised during the reconstruction process.
Many Deep Recon systems offer adjustable parameters, such as denoising strength, allowing for some customization to optimize image quality for specific clinical protocols or challenging patient populations. This flexibility enables clinicians to tailor the reconstruction to achieve the best possible diagnostic images for diverse scenarios.

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