AccuContour

by Manteia Technologies Co., Ltd.  · Based in China → — Physician Workstation with AI-Contouring
Nuclear Medicine Oncology Radiology
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Regulatory Status Disclosed

Overview

AccuContour is an advanced AI-driven auto-contouring solution developed by Manteia Technologies Co., Ltd. specifically for radiation oncology teams. It significantly enhances the accuracy and efficiency of treatment planning by automating the contouring process for Organs-at-Risk (OARs), lymph nodes, and tumor targets. The tool supports the integration of user self-trained models to adapt to specific clinical needs.

Beyond auto-contouring, AccuContour offers robust features for fusion and registration of multi-modal images, including CT, MRI, PET-CT, and 4D imaging, ensuring precise alignment for comprehensive treatment planning. It also provides a vendor-independent platform for reviewing various treatment plans (3D, IMRT, VMAT, Tomo plans), complete with one-click dose constraint checks and plan comparison functionalities. Furthermore, the software includes a dose accumulation module that supports deformed dose accumulation, multi-course, adaptive accumulation, and biological dose conversion, streamlining the workflow for radiation therapy.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • AI Auto-Contouring for OARs, lymph nodes, and tumor targets
  • Support for user self-trained models
  • Fusion & Registration for CT, MRI, PET-CT, and 4D images (rigid and deformable)
  • Vendor-independent Plan Review (3D, IMRT, VMAT, Tomo plans)
  • Dose Accumulation (deformed dose, multi-course, adaptive, biological dose conversion)
  • One-Click Dose Constraint Check
  • Plan Comparison
  • High Efficiency (Auto-Contouring in 1 min, Deformable Registration in 15 sec)
  • Full Compatibility with all RT systems and patient demographics
  • Validated Accuracy in over 1200 worldwide centers

Use Cases

  • Radiation therapy treatment planning
  • Treatment evaluation and adaptation
  • Optimizing radiation treatment plans
  • Tracking and analyzing dose distribution across treatments
  • Adaptive Radiation Therapy (ART) workflows
  • Clinical research and validation of auto-segmentation

What Physicians Need to Know

Key Capabilities
AI auto-contouring for over 300 OARs, lymph nodes, and 20+ tumor targets, supporting user self-trained models. Features include fusion and registration for CT, MRI, PET-CT, and 4D images (rigid and deformable), vendor-independent plan review (3D, IMRT, VMAT, Tomo with dose constraint checks), and dose accumulation with DVH analysis and biological dose conversion (BED/EQD2 models). It automates contouring in 1 minute and deformable registration in 15 seconds.
Clinical Utility
Significantly boosts efficiency by over 90% through automation, reducing contouring time and inter-observer variability in radiation therapy planning. It ensures accurate multimodal alignment for precise treatment planning and facilitates comprehensive, vendor-independent plan review. Clinicians have reported that the majority of auto-generated contours can be used directly or require minimal modification.
Integration Options
AccuContour is a vendor-independent and fully interoperable system, designed to seamlessly integrate into existing workflows and compatible with all RT systems. It supports various imaging modalities (CT, MRI, PET-CT, 4D, CBCT) and requires DICOM 3.0 compliance. Deployment options include local Windows workstations, client/server, CITRIX, or cloud-based, with full compatibility as a plug-in for Varian Eclipse v15+.
Compliance Status
The device is FDA 510(k) cleared (K221706, March 9, 2023) as a Class II Medical Image Management and Processing System (Product Code QKB). It also adheres to DICOM 3.0 compliance standards.
Pricing Model
Manteia offers a 30-day free trial for AccuContour. The system is modular, allowing clinics to customize their software by selecting specific modules, with AccuLearning available as an add-on. Specific pricing details are not publicly disclosed.
User Experience
AccuContour features a user-friendly design with no steep learning curve, enabling users to quickly integrate it into their daily workflow to enhance efficiency and accuracy. Testimonials highlight its ability to save hundreds of hours for planners and its favorable recognition by physicians for quality and efficiency.
Implementation Complexity
The system is designed for easy installation on local Windows workstations and offers flexible deployment options (standalone, client/server, CITRIX, cloud). Its modular structure allows for customization of features, naming conventions, colors, and contouring standards via templates, simplifying integration into diverse clinical environments.
Evidence Base
AccuContour is validated and used in daily clinical workflows by over 1200 centers worldwide. Studies demonstrate its accuracy in auto-segmenting OARs in head and neck and abdominal regions, with auto-contouring times as low as 1 minute per patient. It utilizes deep learning-based auto-segmentation with a U-Net architecture, trained on diverse CT datasets. While generally accurate (DSC values around 0.90), some small or low-contrast structures may still require manual review and editing.
Physician Tip

When considering AccuContour, physicians should leverage the 30-day free trial to assess its performance with their specific patient demographics and imaging protocols. While the AI auto-contouring offers significant efficiency gains, particularly for common OARs, it's crucial to maintain a workflow that includes expert review and potential manual editing, especially for complex or small-volume structures like the chiasm, where studies indicate lower initial accuracy. The ability to train custom models with AccuLearning can further enhance precision for unique institutional protocols or specific tumor targets. Utilize its vendor-independent plan review and dose accumulation features to streamline adaptive therapy planning and quality assurance.

AccuContour's strength lies in its vendor-independent and DICOM 3.0 compliant architecture, ensuring broad compatibility with existing RT systems and imaging modalities (CT, MRI, PET-CT, 4D, CBCT). Its flexible deployment options (local, client/server, cloud, or as a Varian Eclipse plug-in) allow for seamless integration into various IT infrastructures. This interoperability minimizes disruption to current workflows and maximizes the utility of existing equipment, making it a versatile addition to any radiation oncology department.

Details

Category Oncology AI, Radiology & Imaging AI
Pricing Contact for pricing — 30-Day Free Trial
DeploymentOn-premise/Desktop (standalone software)
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status 1 AI-estimated

AccuContour (K221706) is a Class II medical device cleared by the FDA on March 9, 2023. It is a standalone software used by radiation oncology departments for multi-modality image registration and (non-contrast) CT image segmentation, generating information for treatment planning, evaluation, and adaptation.
Integrations
EHR Not specified
Specialties Nuclear Medicine, Oncology, Radiology

Ratings & Reviews

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Press & Coverage

FDA 510(k) Premarket Notification Database
AccuContour 4.0 Receives FDA Clearance
Manteia Technologies Co., Ltd. received FDA 510(k) clearance for AccuContour 4.0 on January 23, 2026, a software product designed to assist clinicians in radiation therapy by processing radiological images for accurate identification and delineation of target areas.
2026-01
Frontiers in Oncology (via PMC)
Clinical validation of commercial deep-learning based auto-segmentation models for organs at risk in the head and neck region: a single institution study
A study published on July 11, 2024, clinically validated Manteia AccuContour (version 3.1) for head and neck cancer OAR auto-contouring, reporting high Dice similarity coefficients (DSCs) for many organs and an average contour generation time of 1 minute per patient.
2024-07
Technology in Cancer Research & Treatment (via PMC)
Streamlining Thoracic Radiotherapy Quality assurance: One-Class Classification for Automated OAR Contour Assessment
This article, accepted in May 2025, discusses the use of AccuContouru2122 (Manteia Medical Technologies Co. Ltd.) to generate automated contours for thoracic radiotherapy quality assurance and the development of a model to identify low-quality contours.
2025-05
Manteia Official
Manteia New Website Launch!
Manteia announced the launch of their new official website on April 14, 2025, highlighting their flagship products, including AccuContour, AccuLearning, and Mozi.
2025-04
Frontiers in Oncology (via PMC)
Establishing prospective performance monitoring for real-world implementation of deep learning-based auto-segmentation in prostate cancer radiotherapy
Published in December 2025, this study details the real-world implementation of deep learning-based auto-segmentation in prostate cancer radiotherapy, noting that AccuContour (Model A) from Manteia Medical Technologies Co. was initially used as a trial product.
2025-12
MDPI - Cancers
Comparison of Two Auto-Contouring Systems for Head and Neck Organs at Risk to Institutional Reference Standard in Radiotherapy Planning
A study published on June 5, 2026, compared Manteia AccuContour with MIM Protu00e9gu00e9AI for head and neck OAR auto-contouring, with methodologies focusing on manual reference contour generation and primary outcomes including Dice Coefficient and Hausdorff Distance.
2026-06
Manteia Official
AccuContour - AI Contouring, Fusion & Registration, Plan Review, Dose Accumulation
AccuContour offers AI auto-contouring for various anatomical structures, supports fusion and registration of multi-modality images, provides vendor-independent plan review, and includes dose accumulation features for radiation oncology departments.
unknown
RT Medical Systems
Best AI Auto-Contouring Software for Radiotherapy 2026
This June 2026 article reviews AI auto-contouring software for radiotherapy, mentioning Manteia AccuContour as a tool that offers AI auto-contouring and advises evaluating its product name, indications, modalities, and integrations directly with the vendor.
2026-06

Videos

Product demos, reviews, and walkthroughs for AccuContour.

View all on YouTube

Frequently Asked Questions

AccuContour is designed to integrate seamlessly into existing clinical workflows, often reducing manual contouring time significantly, for example, from 90 minutes to 20 minutes per patient in radiation therapy. It typically supports various medical imaging modalities such as CT and MRI, utilizing deep learning algorithms to automatically outline anatomical structures. The integration can be automated, with contours becoming available in minutes within your existing treatment planning system.
For any AI medical device like AccuContour, FDA clearance or CE marking is crucial, as the FDA regulates AI/ML software as medical devices. To ensure patient data privacy and HIPAA compliance, AccuContour would need to implement robust safeguards such as end-to-end encryption, role-based access controls, comprehensive audit trails, and secure data storage. Vendors handling Protected Health Information (PHI) must also have a Business Associate Agreement (BAA) in place.
Key differentiators among AI contouring solutions often include the speed and accuracy of contour generation, the number of organs-at-risk (OARs) and lymph nodes supported, and specialized features like active intelligence for GTV contouring. Some systems may offer superior educational resources, comprehensive automation for treatment planning, or robust local processing for privacy-prioritized environments. Performance can also vary based on training data, neural network architecture, and specific contour definitions.
Pricing models for healthcare AI software like AccuContour commonly include subscription-based fees, which can be monthly or annually, and may scale with the number of users or providers. Additional costs can arise from deployment type (cloud vs. on-premise), integration with existing systems, specialized support and training, and ongoing maintenance and upgrades. Some vendors may also offer value-based pricing or hybrid models that combine subscription fees with performance incentives.
AI algorithms, including those for contouring, can have limitations such as potential biases stemming from insufficient or biased training data, which might lead to less accurate outcomes for certain patient demographics or unusual anatomies. Poor image quality can also significantly impact diagnostic accuracy. While AI can handle many complex cases, there may be instances where unusual anatomies or pathologies lead to less optimal results, requiring careful human review.
Human oversight is crucial and recommended for AI tools like AccuContour, as AI should augment, not replace, clinical judgment. Physicians are expected to review and approve all AI-generated contours, especially since AI can sometimes produce incorrect or misleading outputs. This oversight ensures accuracy, contextual relevance, and compliance with regulatory standards, particularly in complex medical scenarios.
The medico-legal landscape for AI in healthcare is evolving, with limited guidance addressing liability when AI is used in clinical practice. Physicians relying on AI findings, if incorrect, may face implications for patient harm, raising questions about the relevant standard of care. There are concerns about automation bias, where physicians might over-rely on AI results without critical evaluation, and the difficulty in determining accountability for AI-caused medical injuries due to the 'black box' nature of some AI.

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Suggest an Edit → | Last Verified: 2026-04-18 | First Added: 2026-04-18
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