Brainlab Elements Image Fusion

by Brainlab AG  · Based in Germany → — Pioneering software-driven medical technology for image-guided surgery and radiosurgery.
Neurosurgery Oncology Radiology
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Regulatory Status Disclosed

Overview

Brainlab Elements Image Fusion is a key application within the comprehensive Brainlab Elements suite, designed to enhance medical image data processing for surgical interventions and treatment planning. This software is renowned for its accuracy and reliability in multi-modality image fusion, providing physicians with improved anatomical insights for vital definition and contouring throughout the body. It facilitates fast, automatic, and accurate co-registration between various image modalities, including CT, MRI, PET, SPECT, and Ultrasound, using both rigid and deformable registration methods.

The Brainlab Elements suite, of which Image Fusion is a part, offers a range of specialized modules. These include Contouring for outlining, refining, and manipulating structures in patient image data; Fibertracking for processing and visualizing cranial white matter tracts based on Diffusion Weighted Imaging (DWI) or Diffusion Tensor Imaging (DTI) data; and BOLD MRI Mapping to analyze blood oxygen level dependent data for visualizing activation signals. Additionally, Elements Image Fusion Angio specifically handles the co-registration of cerebrovascular image data, allowing the fusion of 2D digital subtraction angiography (DSA) sequences with 3D vascular images like MRA, CTA, and 3D DSA to combine flow and location information.

The tool supports patient-specific planning by automatically generating accurate anatomy, leveraging multiple datasets and voxel-based tissue classification. It also incorporates artificial intelligence features for the identification of previously diagnosed lesions or tumors in T1-Weighted Contrast-Enhanced Magnetic Resonance (T1+C MR) volumetric images. Brainlab Elements is a versatile platform that integrates into various clinical workflows, offering solutions for surgical planning, navigation, data management, and intraoperative imaging.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • Multi-modality Image Fusion (rigid and deformable co-registration)
  • Contouring (outlining, refining, manipulating 3D structures)
  • Fibertracking (visualization of cranial white matter tracts)
  • BOLD MRI Mapping (analysis of blood oxygen level dependent data)
  • Image Fusion Angio (co-registration of cerebrovascular image data)
  • Automated Patient Anatomy Segmentation
  • Trajectory Planning (for stereotaxy, DBS, sEEG, biopsies)
  • Post-operative Accuracy Verification
  • AI-powered lesion/tumor identification
  • DICOM data transfer and processing

Use Cases

  • Image-guided surgery planning (cranial, extracranial, neurosurgery, spine)
  • Radiation treatment planning (radiosurgery, radiotherapy)
  • Functional neurosurgery (DBS, sEEG, biopsies)
  • Pre-operative planning and intraoperative navigation
  • Post-operative treatment verification
  • Medical research and troubleshooting

What Physicians Need to Know

Key Capabilities
Provides fully automated and highly accurate image fusion using a mutual information algorithm for rapid dataset correlation. Supports rigid and deformable registration methods for aligning anatomical structures across various modalities including CT, MRI, PET, SPECT, US, and 2D DSA to 3D vascular images. Features include region-of-interest definition, flexible contouring, and advanced 2D/3D visualization. It can also perform automated rigid fusion between preoperative MRI and intraoperative ultrasound, and compensate for brain shift using elastic image fusion algorithms.
Clinical Utility
Aids in image-guided surgery and radiation treatment planning, enhancing pre-surgical planning and radiotherapy. Offers improved anatomical insights for vital definition and contouring, supporting cranial and extracranial surgical and radiotherapy treatments. Provides real-time intraoperative insights, particularly in neurosurgery with integrated ultrasound, to assist in maximizing safe tumor resection even with brain shift. It is also valuable for stereotaxy use cases (DBS, sEEG, biopsies), post-operative accuracy verification, and optimizing treatment planning for multiple brain metastases and spinal bone metastases.
Integration Options
Available as an individual application for streamlined integration into existing clinical workflows. It integrates seamlessly with other Brainlab platforms like Curveu2122 Image Guided Surgery and Buzzu00ae Digital O.R. Supports data transfer to and from PACS and other storage media devices. Offers digital integration with compatible third-party systems, such as Fujifilm's ARIETTA Precision ultrasound, for 'plug-n-play' workflows. Provides multi-platform flexibility, allowing use on various devices including workstations, iPads, and iPhones.
Compliance Status
Brainlab Elements Image Fusion is an FDA-cleared medical device (e.g., 510(k) clearances K223106 and K243633). It demonstrates compliance with safety and performance standards through rigorous verification and validation. It is indicated for processing medical image data to support image-guided surgery and radiation treatment planning, but it is not intended for direct diagnostic purposes or creating physical replicas for diagnosis.
Pricing Model
Brainlab offers flexible business models, ranging from simple, single licenses to multiple offerings across various departments, designed to be scalable to the evolving needs of any department. Specific pricing details are not publicly disclosed.
User Experience
Designed for a user-focused and intuitive experience, incorporating built-in time-saving automation at every step. Features automated pre-selection and pre-calculation of fusion pairs, with tools like Spyglass and Amber blue blending for verification. Multi-platform flexibility enhances ease of planning and review. Effective operation requires trained personnel and high-quality input images, as AI features are dependent on user-set parameters.
Support Quality
Brainlab is stated to provide timely access to Elements and corresponding technical support.
Implementation Complexity
Positioned for easy integration into clinical workflows as an individual application. Seamless integration with other Brainlab platforms and compatible third-party systems (e.g., Fujifilm ultrasound) can streamline setup. Requires a computing environment that meets specific hardware criteria.
Evidence Base
Clinical validation confirms its effectiveness in pre-planning for surgeries and radiotherapy, meeting safety and performance requirements. Performance testing includes software verification, usability evaluations, and accuracy tests, with validation for brain shift compensation (virtual iMRI) and AI-based tumor segmentation on a large patient dataset (412 MR images), demonstrating high precision and Dice similarity coefficients. Studies support its accuracy in automatic segmentation and its utility in navigated 3D ultrasound integration for brain tumor surgery and CT-MRI image fusion for communicative tumors.
Physician Tip

Leverage the automated image fusion capabilities to quickly and accurately co-register multi-modal imaging data, enhancing anatomical understanding for complex cases. Pay close attention to the region-of-interest definition feature to optimize fusion for specific anatomical areas. Utilize the system's ability to compensate for brain shift, especially in neurosurgical procedures, to maintain navigation accuracy throughout the intervention. Ensure proper training for your team to maximize the utility of its advanced features and understand the impact of input image quality on AI-driven functionalities. Integrate intraoperative ultrasound when available to gain real-time updates on patient anatomy. The flexibility to contour on any dataset allows for comprehensive pre-planning across various surgical and radiotherapy scenarios.

Brainlab Elements Image Fusion is designed for flexible integration, both as a standalone application and within the broader Brainlab ecosystem (e.g., Curve, Buzz). Its ability to transfer DICOM data to and from PACS is fundamental for workflow integration. The 'plug-n-play' integration with specific third-party devices, like Fujifilm's ARIETTA Precision ultrasound, highlights a commitment to streamlined, vendor-agnostic workflows where beneficial. Facilities should assess their existing hardware and IT infrastructure to ensure compatibility and optimal performance, as the software has specific computing environment requirements. The multi-platform access (workstation, mobile) further enhances its adaptability within diverse clinical settings.

Details

Category Oncology AI, Radiology & Imaging AI, Surgical AI
Pricing Contact vendor
DeploymentOn-premise (workstation) and cloud-enabled for data storage and sharing
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status 1 AI-estimated

Brainlab Elements 6.0, including Brainlab Elements Image Fusion, Image Fusion Angio, Contouring, BOLD MRI Mapping, and Fibertracking, received FDA clearance (K223106) on July 14, 2023. It is indicated for processing medical image data to support image-guided surgery and radiation treatment planning.
Integrations
EHR Not specified
Specialties Neurosurgery, Oncology, Radiology

What the Web Says

Brainlab Elements Image Fusion is a software application designed for co-registration and fusion of medical image data, such as CT, MRI, PET, SPECT, and US, to assist in image-guided surgery and radiation treatment planning. It is part of the broader Brainlab Elements suite, which provides a comprehensive toolkit for medical professionals, offering automated and highly accurate image fusion for better anatomical insights and enhanced pre-surgical planning. Physicians and healthcare professionals generally view the software as a powerful and flexible tool that enhances precision and control in various surgical and radiotherapy planning scenarios.

Overall: Positive

Strengths

  • Automated and highly accurate image fusion for precise dataset correlation and contouring.
  • Enhances pre-surgical planning and radiotherapy with verified effectiveness.
  • Provides GPS-level precision for brain and spinal surgeries, aiding in avoiding damage to vital areas.
  • Offers multi-platform flexibility, allowing access and planning on various devices, including mobile.
  • Streamlines pre-planning workflow with intuitive modules, transforming image preprocessing into actionable treatment plans.
  • Supports collaboration across departments and locations, enhancing workflow efficiency.

Limitations

  • Dependency on proper hardware and user expertise for effective operation.
  • AI features depend heavily on input image quality and user-set parameters.
  • Not intended for direct diagnosis or creating physical replicas from image data for diagnostic purposes.
  • Some users on Reddit find other CAD software unintuitive, which might extend to complex medical imaging software.
  • Potential for large maximum rotational misalignments in frameless radiosurgery, highlighting the need for real-time monitoring.
  • No specific cons found from G2 or Capterra directly related to Brainlab Elements Image Fusion, but general concerns about slow review publishing and bias exist on Capterra.

Based on reviews from: Medical News Observer, accessdata.fda.gov, YouTube (Brainlab Elements: The Software Revolutionizing Modern Surgery), Brainlab - PDF Catalogs | Technical Documentation, accessdata.fda.gov (K223106), PMC (Mixed reality with 3D brain imaging for patient consultation in neurosurgery: an IDEAL stage 2a feasibility study), Brainlab (Functional Neurosurgery Planning Solutions), Brainlab (Fully Automated and Highly Accurate. IMAGE FUSION), Frontiers (Evaluation of a Dedicated Software u201cElementsu2122 Spine SRS, Brainlabu00aeu201d for Target Volume Definition in the Treatment of Spinal Bone Metastases With Stereotactic Body Radiotherapy), Brainlab (Experience Innovations in Imaging, Image Review and Planning), Brainlab and Fujifilm Integrate Cutting-Edge Technology, Offering Advanced Capabilities to Neurosurgery Clinicians in the U.S., G2 (Capterra Pros and Cons | User Likes & Dislikes), PMC (Mixed Reality as a Digital Visualisation Solution for the Head and Neck Tumour Board: Application Creation and Implementation Study), PubMed (Intrafraction motion during frameless radiosurgery using Varian HyperArcTM and BrainLab ElementsTM immobilization systems), G2 (Brainlabs (formerly Nabler) Reviews 2026: Details, Pricing, & Features), Brainlab (Experience the Latest in Image Review, Intraoperative Spine Imaging and Navigation), Reddit (r/MachineLearning - [P] Image Fusion Techniques for Image classification Task), G2 (Best AI Medical Diagnostic Platforms: User Reviews from July 2026), Indeed.com (Working at Brainlab: Employee Reviews), Reddit (r/Fusion360 - Fusion alternatives for different brains?), Reddit (Looking for an AI photo editor that can add elements to existing photos, not just regenerate them.), Reddit (r/cognitiveTesting - Brainlabs.me , any good?), Reddit (r/generativeAI - Best free AI program for creating/editing images?)

Last updated: 2026-07-17

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Videos

Product demos, reviews, and walkthroughs for Brainlab Elements Image Fusion.

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Frequently Asked Questions

Brainlab Elements Image Fusion utilizes AI primarily for the identification of previously diagnosed lesions or tumors within T1-Weighted Contrast-Enhanced Magnetic Resonance (T1+C MR) volumetric images. The system also offers automated rigid fusion between preoperative MRI and intraoperative ultrasound images, with ongoing research and development into more advanced elastic fusion techniques.
Brainlab Elements Image Fusion is classified as a Class II medical device and has received FDA 510(k) clearance, demonstrating its adherence to established safety and performance standards. Brainlab also prioritizes data privacy and security, employing a HIPAA/Security & Data Privacy Officer and implementing measures like encryption and pseudonymization for its cloud services to ensure compliance with regulations like HIPAA.
A primary limitation is the system's dependency on appropriate hardware and the expertise of trained personnel for effective operation and accurate interpretation of processed images. Furthermore, while powerful, image fusion itself can introduce inaccuracies, particularly with rigid fusion in areas like the spine where anatomical shifts can occur, and the quality of AI features relies heavily on the input image quality and user-defined parameters.
Brainlab Cloud Services, which can integrate with Elements Image Fusion, employs a dedicated HIPAA/Security & Data Privacy Officer and trains all employees on HIPAA and data privacy protection. Patient data is secured through SSL encryption during transfer and storage, advanced key management, access control systems, and the option for pseudonymization of patient information.
Yes, the multimodal image fusion software market includes several key players such as GE HealthCare, Siemens Healthineers, Philips Healthcare, Canon Medical Systems, and Fujifilm Healthcare. Other alternatives offering advanced imaging and planning capabilities, some with AI integration, include Elucis by Realize Medical, Materialise Mimics, SenseCare by SenseTime, and Axial3D.
Specific pricing models or cost structures for Brainlab Elements Image Fusion are not publicly disclosed in detail, as prices can vary significantly by country and are subject to changes in raw material costs and exchange rates. However, market trends indicate that pricing models for multimodal image fusion software are evolving, influencing hospital buying decisions and return on investment evaluations.
Yes, Brainlab Elements Image Fusion is designed to perform both rigid and deformable registration methods for co-registering image data. While the core fusion algorithms provide fast and accurate co-registration, AI features specifically enhance the process by identifying lesions or tumors in MR images, and ongoing development aims to advance capabilities like elastic fusion for improved accuracy in complex cases such as spinal surgery.

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