Precise Image
by Philips Medical Systems Nederland
· Based in Netherlands →
— AI-powered CT image reconstruction for enhanced quality and lower dose.
Contact vendor for pricing
Regulatory Status Disclosed
Overview
Philips Precise Image is an artificial intelligence (AI)-based reconstruction technique for Computed Tomography (CT) imaging. It is designed to produce high-quality images with a familiar appearance, similar to traditional filtered back projection (FBP) images, while incorporating noise-reduction capabilities.
This tool is intended for use by radiologists and other healthcare professionals in care settings where CT imaging is performed. It aims to support diagnostic confidence across various clinical applications, including body, head, and cardiac imaging, as well as radiotherapy planning.
Within a clinical workflow, Precise Image integrates into the CT imaging process from scan preparation to post-processing. It offers fast reconstruction speeds, with most reference protocols reconstructed in under one minute. This allows for rapid processing of patient data to support high-throughput clinical workflows.
Notable capabilities include its use of a deep-learning convolutional neural network (CNN) trained on clinical data to maintain an FBP-like image texture. Precise Image offers five levels of noise reduction (smoother, smooth, standard, sharp, and sharper), allowing clinicians to select options based on specific preferences and clinical requirements. It is also designed to enable lower radiation doses while maintaining or improving image quality.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- AI-powered CT image reconstruction using convolutional neural networks (CNN)
- Reduces radiation dose in CT scans
- Lowers image noise
- Improves low-contrast detectability
- Provides fast reconstruction speed
- Reproduces traditional filtered back-projection (FBP) image appearance
- Offers user-adjustable settings for dose reduction and image quality
- Validated by internal clinical specialists and external board-certified radiologists
- Integrated with Philips CT systems, such as the CT 5300
Use Cases
- Diagnostic CT imaging for head, whole body, and vascular applications in adults
- Improving image quality in low-dose CT scans
- Enhancing diagnostic confidence for radiologists
- Streamlining CT examination workflows
- Supporting cardiac programs and ultra-low dose screening
What Physicians Need to Know
DICOM Support & Standards
Philips' PACS solutions support both DICOM and non-DICOM data. Philips also actively contributes to DICOM standards, particularly for digital pathology, and offers DICOM export capabilities.
PACS Integration Method
Philips' Precise Image is part of a broader radiology workflow that integrates with PACS. Philips offers an integrated PACS Diagnostic Workspace, providing radiologists with access to tools, advanced visualization, and AI-enabled insights within a single workspace. Philips AI Manager also integrates with existing IT infrastructure and PACS solutions.
Reading Room Workflow Impact
Precise Image aims to improve diagnostic confidence and reduce radiologist fatigue. It streamlines workflows from image acquisition to reporting through AI-enabled image reconstruction and automated patient positioning. The solution helps manage the delivery of reports by matching radiologist strengths to patient needs, expediting reading and reporting.
AI Model Architecture (deep learning approach)
Precise Image utilizes Artificial Intelligence, specifically Convolutional Neural Networks (CNNs) and deep learning neural networks, for image reconstruction. It employs a supervised learning process where neural networks are trained using routine-dose scans to generate low-dose scans with noise textures resembling filtered back projection (FBP) while retaining noise reduction capabilities.
Processing Speed (per study)
Precise Image offers fast AI-based reconstruction, with all reference protocols reconstructed in under one minute, and average reconstruction times for common protocols being 30 seconds or less.
FDA Clearance Pathway (510k/De Novo)
Precise Image reconstruction software for CT systems received FDA 510(k) clearance. Philips also received FDA 510(k) clearance for SmartSpeed Precise, an AI-powered MRI software, and Spectral CT Verida.
Supported Modalities (CT/MRI/X-ray/US)
Precise Image is primarily associated with CT systems, indicated for head, whole body, and vascular X-ray Computed Tomography applications. Philips also offers AI-powered solutions like SmartSpeed Precise for MRI and AI advancements in general imaging ultrasound.
Sensitivity & Specificity Data
Precise Image simultaneously achieves up to 80% lower radiation dose, 85% lower noise, and 60% improved low-contrast detectability compared to conventional image reconstruction. Detectability with Precise Image at 4 mGy is more than 80% better than FBP at 10 mGy, and at 2 mGy, it's more than 43% better than FBP at 10 mGy.
RSNA/ACR Validation
Philips showcased its AI-powered diagnostic and treatment imaging innovations, including the CT 5300 system with Precise software solutions, at RSNA 2024. Image quality of Precise Image is objectively assessed using an ACR 464 phantom.
Physician Tip
Precise Image can significantly reduce radiation dose while maintaining or improving image quality, which is beneficial for patient safety. The AI-powered reconstruction provides images with a familiar FBP-like appearance, easing radiologist adaptation. Its fast processing speed can enhance workflow efficiency in busy departments. For optimal results, leverage the 5 user-adjustable settings to match specific diagnostic preferences.
Precise Image is part of Philips' broader 'Precise Suite' and 'CT Smart Workflow' solutions, designed for end-to-end integration from image acquisition to reporting. It integrates with Philips' Advanced Visualization Workspace and PACS solutions, allowing for a unified workflow and access to AI-enabled insights within the diagnostic environment. Philips also offers AI Manager for streamlined integration of third-party AI applications.
Details
| Category | Radiology & Imaging AI |
| Pricing | Contact vendor for pricing |
| Deployment | Integrated software application on Philips Computed Tomography (CT) X-Ray Systems. |
| Compliance | |
| BAA Available | Unknown AI-estimated |
| HIPAA Compliant | Unknown AI-estimated |
| FDA Status | Cleared AI-estimated |
| Integrations | |
| EHR | Not specified |
| Specialties | Radiology |
What the Web Says
Philips Precise Image is an AI-based image reconstruction technology for CT and MRI scans designed to enhance image quality and enable lower radiation doses. It utilizes deep learning neural networks to produce high-quality images with reduced noise and improved low-contrast detectability, while maintaining a familiar image appearance. The technology aims to improve diagnostic confidence and efficiency in medical imaging workflows.
Overall: PositiveStrengths
- Improved diagnostic confidence due to enhanced low-contrast detectability and reduced noise.
- Allows for significant reduction in radiation dose (up to 80%) while maintaining or improving image quality.
- Faster scan times (up to 3 times faster) leading to increased productivity and patient throughput.
- Provides sharper images (up to 80% sharper) for clearer visualization and more accurate diagnoses.
- Maintains a familiar image texture similar to traditional filtered back projection (FBP) while offering noise reduction.
- Offers various tools for post-processing studies, including analysis of vessels, measurements, and pulmonary nodules.
Limitations
- Potential for distortions if dose reduction is set too low.
- Some users on Reddit have expressed concerns about the software's aesthetic and limited post-processing capabilities.
- The significant capital investment required for Philips CT scanners, which incorporate this technology, can be a drawback for smaller institutions.
- One Reddit user noted slow scout/surview scan times on Philips CT scanners.
- One Reddit user mentioned that Philips CT scanners might not be ideal for very tall patients due to short scan range.
Based on reviews from: physicianaitools.com, capterra.co.uk, g2.com, capterra.co.il, capterra.com.au, bestguide.com, scribd.com, elion.health, reddit.com, practical-patient-care.com, philips.ae, itnonline.com, nih.gov, philips.com, philips.co.uk, sectorpunk.com
Last updated: 2026-10-31
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Press & Coverage
philips.com
Philips Reaches 1,000 SmartSpeed Precise Installations, Advancing AI-Powered MRI Care
Philips announced that its SmartSpeed Precise, a dual AI-powered technology for accelerating MR imaging and enhancing image quality, has reached 1,000 installations worldwide. This milestone highlights the growing adoption of AI in routine MRI care, with the technology used in at least 95% of compatible clinical scans on equipped systems globally.
2026-10
philips.com
Philips accelerates precise imaging with unique AI technologies in MRI to improve patient outcomes
Philips introduced SmartSpeed Precise, powered by Dual-AI engines, at ECR 2025, significantly improving scan speed and diagnostic image quality across its MR portfolio. This next-generation solution builds on existing Compressed SENSE and SmartSpeed technologies, offering faster scans and higher image quality.
2025-02
philips.com
Philips receives FDA 510(k) clearance for Verida, the world's first AI-powered detector-based spectral CT*, advancing diagnostic precision across clinical applications.
Philips announced FDA 510(k) clearance for its Spectral CT Verida system, which incorporates Spectral Precise Image technology. This system combines AI-based deep learning reconstruction with a third-generation Nano-panel Precise dual-layer detector to reduce noise and enhance image quality across various CT applications.
2026-04
philips.com
Philips Advances MRI Speed and Precision with FDA 510(k) Clearance of SmartSpeed Precise Dual AI Software
Philips received FDA 510(k) clearance for SmartSpeed Precise, its latest deep learning reconstruction software for MRI, marking a significant step towards autonomous and personalized MRI. This dual AI solution delivers up to three times faster scanning and up to 80% sharper images.
2025-07
appliedradiology.com
Philips Launches New CT System, AI-Enabled Imaging Tools and Cloud-Based Informatics
At RSNA 2024, Philips unveiled the CT 5300 system, featuring a comprehensive suite of AI-enabled 'Precise' software solutions, including NanoPanel Precise detector and ultra-low noise Precise Image reconstruction technology. These innovations aim to make high-quality care more productive, cost-effective, and widely accessible.
2024-12
scribd.com
Precise Image: AI-based CT image reconstruction
This document describes Philips' Precise Image, an advanced AI-enabled CT image reconstruction algorithm that trains neural networks on routine-dose scans to generate low-dose scans with noise reduction and a familiar appearance. It aims to improve diagnostic confidence at half the dose.
unknown
nih.gov
Comparison of Philips Precise Image and GE TrueFidelity Deep Learning Reconstruction Algorithms in Low-Dose CT: A Quantitative Phantom Study
A study compared Philips Precise Image (PI) and GE TrueFidelity (TF) deep learning reconstruction algorithms in low-dose CT using an 80 kVp low-dose CT scenario. The study found that TF-High offered the optimal balance of noise suppression and structure fidelity, while PI-Sharper highlighted fine detail enhancement.
2025-09
nih.gov
Evaluation of a deep learning reconstruction algorithm (Precise Image) for abdominal CT: a phantom study
This study confirms that the Philips Precise Image algorithm reduces image noise and improves contrast-to-noise ratio, overall image quality, and lesion conspicuity compared with iterative reconstruction algorithms in abdominal CT. The highest image quality and lowest noise were observed with the highest level of Precise Image.
2023-03
Videos
Product demos, reviews, and walkthroughs for Precise Image.
Evolution of the Philips MRI Technology
Frequently Asked Questions
Philips Precise Image employs AI, specifically deep-learning reconstruction (DLR) techniques, to enhance CT and MRI image quality. For CT, it uses a trained deep-learning neural network to produce low-noise images from low-dose scans, aiming for an image appearance similar to traditional filtered back projection (FBP) images. In MRI, Philips SmartSpeed Precise integrates dual AI engines to accelerate scanning by up to three times and deliver up to 80% sharper images.
Philips Precise Image offers several benefits, including significant radiation dose reduction in CT while maintaining or improving image quality and diagnostic confidence. For MRI, SmartSpeed Precise enables faster scan times and sharper images, which can lead to increased patient throughput and potentially better visualization for diagnosis.
Philips SmartSpeed Precise for MRI has received FDA 510(k) clearance for clinical use across Philips' 1.5T and 3.0T MRI systems. Philips Precise Image for CT systems has also received FDA 510(k) clearance, demonstrating substantial equivalence to predicate devices and compliance with relevant standards. It's important to note that regulatory status can vary by region and specific product versions.
Philips aims for seamless integration of its AI solutions, including Precise Image, into existing radiology workflows. Philips AI Manager is designed as an end-to-end AI enablement solution that integrates with existing IT infrastructure and PACS, allowing radiologists to leverage various AI applications. The Philips radiology image management PACS Diagnostic Workspace also provides access to AI-enabled insights and tools.
While Philips Precise Image offers significant advancements, some limitations exist. For CT, Precise Image has been evaluated and is available on preselected reference protocols for adult subjects and is not indicated for use in pediatric subjects. For MRI, while SmartSpeed Precise improves sharpness, structures smaller than the acquisition voxel size cannot be retrieved, ensuring the networks do not invent features.
The radiology AI market is dynamic, with various vendors offering AI-powered image reconstruction and analysis tools. While Philips highlights the unique aspects of Precise Image, such as its dual AI solution for MRI and its FBP-like image appearance for CT, other manufacturers also offer deep learning reconstruction techniques. Specific alternatives would depend on the modality (CT or MRI) and the desired clinical application.
Philips Precise Image for CT utilizes a supervised learning process to train a convolutional neural network (CNN). This involves training the CNN to reproduce the image appearance of routine-dose FBP images using low-dose scan data, which is generated from routine-dose clinical scans through a sophisticated low-dose simulation technique. Philips emphasizes using primarily clinical images in the training procedure to ensure improved clinical results rather than just good phantom results.
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| Last Verified: 2026-04-19 | First Added: 2026-04-19