Auto Positioning
by GE Hangwei Medical Systems Co., Ltd.
· Based in China →
— AI-based Auto Positioning for Enhanced CT Workflow and Patient Safety
N/a (integrated feature of ge ct systems)
Regulatory Status Disclosed
Overview
Auto Positioning is an advanced AI-based feature developed by GE Hangwei Medical Systems for integration with GE Computed Tomography (CT) systems. This innovative technology leverages a 2D/3D video camera and deep learning algorithms to automate and streamline the patient positioning process for CT examinations.
The system works by deterministically producing a 3D surface contour map of the patient’s body, detecting anatomical landmarks, and identifying patient orientation. Based on this data and the selected imaging protocol, Auto Positioning automatically calculates and adjusts the CT table elevation for optimal centering, and visually displays scout scan start and end locations.
Key benefits include significant workflow improvement through minimizing manual positioning actions, consistent image quality by auto-centering, and optimized radiation dose. Furthermore, it enhances patient safety by detecting potential patient-gantry collisions and identifying patient orientation mismatches, which helps prevent incorrect image annotation.
It is important to note that this tool is a medical device feature for imaging systems and is not an AI tool for a physician directory.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- AI-based deep learning for anatomical landmark detection
- 3D camera for patient body contour mapping and depth information
- Automated patient centering and table elevation calculation
- Patient orientation identification and mismatch warnings
- Patient-gantry collision check for enhanced safety
- Streamlined workflow with single-click operation
- Reduced patient positioning time
- Consistent image quality and optimized radiation dose
- Integration with GE CT systems
- Automated scout scan start and end locations
Use Cases
- Automating patient setup for CT examinations
- Improving workflow efficiency in radiology departments
- Enhancing patient safety during CT scans
- Ensuring consistent image quality across different operators
- Reducing radiation dose through optimized centering
- Minimizing medical errors related to incorrect patient orientation
What Physicians Need to Know
DICOM Support & Standards
GE Healthcare's Auto Positioning, particularly in post-processing applications like 'Head Auto Views', leverages and depends on DICOM services and capabilities, taking DICOM data as input. GE's True PACS also features a flexible, standards-based architecture for tight connectivity with various third-party systems, implying DICOM compatibility for image transfer.
PACS Integration Method
AI-driven tools like 'Spine Auto Views' and 'Head Auto Views' automatically network reformatted series to prescribed DICOM destinations, indicating direct integration with PACS for efficient image transfer. The Edison Open AI Orchestrator is designed to seamlessly integrate clinical AI applications into the radiology PACS reading workflow. True PACS is designed to easily integrate with innovative AI-enabled tools.
Reading Room Workflow Impact
Auto Positioning significantly improves workflow by minimizing patient positioning actions to a single-click operation, representing an 80% reduction in clicks compared to manual methods and potentially reducing overall exam time by 21%. It ensures consistent image quality through auto-centering with a 3D camera, optimizing radiation dose and reducing the need for re-scout scans. The tool also enhances patient safety by performing patient-gantry collision checks and avoiding medical errors through patient orientation identification. It reduces technologist effort and physical strain, allowing more time for patient interaction.
AI Model Architecture (Deep Learning Approach)
Auto Positioning utilizes deep learning algorithms, specifically two distinct networks (RGBLandmarkNet and DepthLandmarkNet) that process 2D video and 3D depth images, respectively. These algorithms automatically detect eight anatomical landmarks on the patient's body to determine orientation and scout scan locations. The system leverages a 3D camera and real-time depth-sensing technology to generate a 3D patient model. The algorithms are trained on diverse datasets from volunteers to ensure broad applicability.
Processing Speed (per study)
The AI-based Auto Positioning significantly reduces patient positioning time. A study showed positioning time was reduced by 28% (from 40.0 u00b1 11.0 seconds manually to 29.0 u00b1 7.0 seconds with AI). The process is streamlined to a single-click operation.
FDA Clearance Pathway (510k/De Novo)
GE HealthCare's AI-based Auto Positioning has received 510(k) clearance from the U.S. FDA. It is one of over 100 FDA-authorized AI-enabled medical devices from GE HealthCare, which has consistently led in AI-related FDA clearances.
Supported Modalities (CT/MRI/X-ray/US)
Auto Positioning is primarily implemented in Computed Tomography (CT) systems (e.g., Revolution Maxima, Revolution Ascend) and also supports Positron Emission Tomography/CT (PET/CT) devices (e.g., Revolution Apex platform, Omni Legend). It is also available on fixed X-ray systems (Definium Tempo, Definium Pace Select ET) and has been integrated into new MRI systems (SIGNA One, SIGNA Sprint, SIGNA Bolt) for automated patient positioning.
Sensitivity & Specificity Data
Clinical data indicates a 94% accuracy for auto-centering the patient within +/- 2cm. A study comparing AI-based automatic positioning with manual positioning in CT showed a significantly higher positioning accuracy of 99.0% for the AI method compared to 92.0% for manual positioning. This improved accuracy also led to a 16% radiation dose reduction and 9% image noise reduction.
RSNA/ACR Validation
GE HealthCare launched its AI-based Auto Positioning technology at RSNA 2019 and continues to highlight its AI-forward imaging platforms, including those with Auto Positioning, at subsequent RSNA annual meetings.
Physician Tip
Leverage Auto Positioning to standardize patient setup, reduce variability in image quality, and minimize radiation dose. The single-click operation frees up technologist time, allowing for increased patient interaction and throughput. Pay attention to the patient orientation identification feature to prevent mislabeling. While primarily for technologists, understanding its capabilities can help physicians appreciate the consistency and quality of acquired images.
GE Healthcare's Auto Positioning is deeply integrated within its CT, PET/CT, MRI, and X-ray systems, forming part of the 'Effortless Workflow' suite. It seamlessly integrates with the imaging system's console and utilizes DICOM standards for data exchange, allowing for automated networking of reformatted series to PACS. The Edison Open AI Orchestrator further facilitates the integration of such AI applications into existing radiology PACS workflows.
Details
| Category | Radiology & Imaging AI |
| Pricing | N/a (integrated feature of ge ct systems) — N/A |
| Deployment | Integrated into GE CT systems (on-premise with the CT scanner). |
| Compliance | |
| BAA Available | Unknown AI-estimated |
| HIPAA Compliant | Unknown AI-estimated |
| FDA Status |
1 AI-estimated The Auto Positioning feature received FDA 510(k) clearance (K192956) on January 16, 2020. It is regulated under 21 CFR 892.1750 (Computed tomography x-ray system) and classified as a Class II medical device. |
| Integrations | |
| EHR | Not specified |
| Specialties | Radiology |
Ratings & Reviews
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Press & Coverage
GE HealthCare News Release
GE HealthCare drives growth with investment in AI-enabled medical devices and tops FDA's list of AI authorizations for 4th Year with 100
GE HealthCare announced it has topped the FDA's list of AI-enabled medical device authorizations for the fourth consecutive year, with AI-based Auto Positioning being one of the highlighted solutions. This technology uses deep learning to automatically detect anatomical landmarks for faster patient positioning in CT and PET/CT devices.
2025-07
GE HealthCare News Release
GE HealthCare's Photonova Spectra photon-counting CT receives FDA clearance
GE HealthCare received FDA 510(k) clearance for its Photonova Spectra photon-counting CT system, which includes automated features like Auto Positioning to improve consistency and simplify the CT process. This system aims to redefine decision-making and care delivery through enhanced image quality and streamlined workflows.
2026-03
Imaging Technology News
GE Healthcare Introduces Revolution Ascend CT System | Imaging Technology News
GE Healthcare unveiled the Revolution Ascend CT System with Effortless Workflow, featuring AI-based Auto Positioning that uses real-time depth-sensing technology and deep learning to accurately position patients with a single click. This system aims to increase operational efficiency and provide more personalized care.
2021-09
GE HealthCare News Release
GE Healthcare releases next-generation premium fixed X-ray system to bring a 'personal assistant' to radiology departments
GE Healthcare launched its next-generation Definium 656 HD fixed X-ray system, which incorporates 5-axis motorization and auto-positioning for fast, automatic positioning to reduce technologist strain and speed up workflows. The system aims to deliver consistent, efficient, and highly automated imaging exams.
2022-08
AuntMinnie
GE HealthCare again tops FDA AI device list - AuntMinnie
GE HealthCare has led the U.S. FDA's list of AI-enabled medical device authorizations for the fourth consecutive year, with 100 authorizations. This includes AI-based Auto Positioning for CT and PET/CT scanners, demonstrating innovation across various imaging modalities.
2025-07
ICE Magazine
GE Healthcare AI-Based Auto Positioning for CT - ICE Magazine
GE Healthcare's AI-based Auto Positioning for CT, available on the Revolution Maxima CT system, allows technologists to position patients with a single click. This hands-free positioning helps expedite exams and minimize exposure, particularly relevant during the COVID-19 pandemic.
2020-07
PMC (PubMed Central)
A comparison between manual and artificial intelligenceu2013based automatic positioning in CT imaging for COVID-19 patients - PMC
A study published in PMC compared manual and AI-based automatic positioning in CT imaging for COVID-19 patients, concluding that AI-based automatic positioning significantly reduced total positioning time by 28% and improved positioning accuracy, leading to a 16% radiation dose reduction.
unknown
GE HealthCare News Release
GE HealthCare Increases Access to Precision Care Tools, Encouraging the Continued Adoption and Practice of More Personalized Medicine Around the World
GE HealthCare announced efforts to increase access to precision care tools, highlighting Effortless Workflow, an AI-based patient Auto Positioning solution, as a key technology addressing operational and staffing challenges. This solution is part of the Omni platform, designed to be scalable and optimize clinical capabilities.
2024-06
Videos
Product demos, reviews, and walkthroughs for Auto Positioning.
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Frequently Asked Questions
AI-driven 'Auto Positioning' systems are designed to seamlessly integrate with current imaging or surgical platforms, often providing real-time guidance or automated adjustments. Their primary applications include optimizing patient alignment for diagnostic scans, enhancing precision in interventional procedures, and reducing setup times, thereby improving efficiency and patient outcomes.
Compliance is paramount, with systems typically employing robust data encryption, anonymization techniques, and secure access protocols to protect patient information. Vendors must adhere to strict regulatory frameworks, often undergoing third-party audits and requiring Business Associate Agreements to ensure data integrity and privacy.
While AI systems provide assistance, the physician remains ultimately responsible for patient care decisions and outcomes, as they have a duty to independently apply the standard of care. Legal frameworks are evolving, but current understanding places accountability with the clinician who oversees and validates the AI's output, though developers and healthcare systems may also share liability.
Traditional patient positioning relies on manual techniques, physical aids, and human expertise, which can be time-consuming and prone to variability. While these methods are well-established, 'Auto Positioning' aims to enhance precision, consistency, and potentially reduce radiation exposure or procedural time through automated, contactless image acquisition.
Cost models for 'Auto Positioning' systems can vary, often involving an initial capital expenditure for hardware and software licenses, followed by recurring fees for maintenance, updates, and technical support. Development costs for a single algorithm can range from $100k-$500k, with implementation adding $50k-$200k, and annual maintenance typically 15-20% of initial development costs.
Limitations can include challenges with unusual patient anatomies, artifacts, or unexpected movements, potentially leading to suboptimal positioning. AI models can also inherit biases from their training data, which might affect performance in diverse patient populations or specific clinical contexts, potentially exacerbating healthcare disparities.
Reputable 'Auto Positioning' systems should have extensive clinical validation, including peer-reviewed studies demonstrating their accuracy, safety, and impact on patient outcomes across varied demographics. Rigorous validation often requires randomized controlled trials, external testing, and continuous monitoring to ensure generalizability and prevent model drift in real-world settings.
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| Last Verified: 2026-04-18 | First Added: 2026-04-18