Fusion7D registers pairs of anatomical and functional volumetric images (e.g. MRI-SPECT, MRI-PET, CT-SPECT, CT-PET), or pairs of anatomical volumetric images (e.g. MRI-MRI, CT-CT and MRI-CT) as a means to ease the comparison of image volume data by the clinician. The result of the registration operation aims to help the clinician obtain a better understanding of the joint information that would otherwise have to be compared visually. This is useful for a wide range of clinical and therapeutic applications. It is important to note that the clinician retains the ultimate responsibility for making the pertinent diagnosis based on their standard procedures including visual comparison of the separate unregistered images. Fusion7D is a complement to these standard procedures.
Device Story
Fusion7D is PC-based software for multi-modality image registration and visualization. It accepts volumetric DICOM data from anatomical (CT, MRI) and functional (PET, SPECT) imaging modalities. The device performs rigid body registration (3D translation and rotation) via manual, semi-automatic (landmark-based), or automatic methods. The software provides a GUI for orthogonal slicing, zooming, panning, window/level control, and image overlays (transparency/thresholding). Clinicians use the registered output to visualize joint anatomical and functional information, aiding in clinical and therapeutic decision-making. The device serves as a complement to standard diagnostic procedures; the clinician retains ultimate responsibility for diagnosis based on visual comparison of original unregistered images.
Clinical Evidence
No clinical data provided. Substantial equivalence is based on technological characteristics and intended use comparisons to legally marketed predicate devices.
Technological Characteristics
PC-based software; DICOM-compliant; rigid body transformation (3D translation and rotation) registration engine; GUI-based visualization (orthogonal slicing, panning, zooming, window/level, overlays).
Indications for Use
Indicated for clinicians requiring geometric alignment and visualization of anatomical (MRI, CT) and functional (SPECT, PET) volumetric image pairs to facilitate comparison of joint information for clinical and therapeutic applications.
Regulatory Classification
Identification
A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.
Special Controls
*Classification.* Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).
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# FUSION 7D 510(K) SUMMARY SECTION
| Date: | 7th February, 2002 |
|--------------------------|---------------------------------------------------------------------------------------------------------------|
| Submitters Name: | Mirada Solutions Ltd. |
| Submitters Name: | Oxford Centre for Innovation.<br>Mill Street, Oxford OX2 OJX, United Kingdom. |
| Submitters Contact: | Dr. Nick Cerneaz, VP Engineering.<br>Tel: 44-1865-811125 Fax: 44-1865-793165 |
| Submitters Contact USA: | Mr. Roger Barnes, rogerb@cswnet.com<br>Tel. 501 525 86 39 Fax: 501 525 86 12 |
| Device Proprietary Name: | Fusion7D |
| Common Name of Device: | Multi-modality Registration Workstation Software |
| Classification Name: | Class II: Picture Archiving and Communications System<br>(892 2050) Product Code: LLZ Image Processing System |
# Critical Definitions:
| Image Registration | The alignment of one or more [medical] images to a reference image<br>in order to facilitate geometric comparison. This is a numerical<br>operation that results in the computation of an explicit mathematical<br>transformation between every point in the registered image sets. |
|--------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Image Fusion | Registration forms the basis of image fusion in the sense that the<br>geometrical alignment of images is a prerequisite. The notion of<br>"fusion" takes this a step further by considering how to visualize the<br>content of different images representing the same object [organ,<br>anatomical region, etc.]. Such techniques include the use of overlays,<br>semi-transparent renderings, etc. |
NOTE: In the context of this application, the term "registration" and "fusion" may be used interchangeably to describe geometric alignment of images and subsequent visualization.
# Device description:
Fusion7D is a software program running on a PC platform, which brings into alignment (registers) pairs of images from different imaging modalities. Fusion7D also includes functionality to read, display, and save the original volumetric data and the results of the registration operation by means of a graphic user interface that includes visualization, file browsing and control of input and output as described in the following text.
# Registration Engine
Medical images can be divided into anatomical images (e.g. CT and conventional MRI), and functional images (e.g. SPECT and PET). Fusion7D provides two registration solutions: 1. It enables the comparison of pairs of anatomical images (to assess changes in anatomical structures) and 2. It correlates the structures seen in an anatomical dataset with the activity detected in functional images.
{1}------------------------------------------------
| Anatomical<br>to Anatomical | | Anatomical<br>to Functional | |
|-----------------------------|--------|-----------------------------|--------|
| Source | Target | Source | Target |
| MRI | MRI | MRI | PET |
| MRI | CT | MRI | SPECT |
| CT | CT | CT | PET |
| | | CT | SPECT |
Fusion7D is therefore useful to register the following pairs of datasets:
The registration operation can be a) manual: whereby the user defines the transformation that brings the two datasets into as close alignment as possible, b) semi-automatic: in which the user inputs a series of landmarks in one dataset and the software provides matching landmarks in the other, and c) automatic: in which the software requires no user input and finds the transformation between the two datasets based on the characteristics of the images. In all these cases the transformation is limited to a rigid body deformation (i.e. 3D translation and rotation).
#### Data/Image Browsing and Visualization
The Fusion7D software incorporates standard visualization facilities to visualize the input DICOM data and the results of the registration operations. This simple visualization GUI includes:
- orthogonal and any-plane slicing of the volumetric data (but no 3D reconstruction), .
- . whole and region of interest zooming,
- panning. .
- . window and level controls,
- image overlays for which the transparency, threshold and colormap is user controlled. ●
The Fusion7D software allows the registration results to be displayed in a variety of ways including: the overlay of one dataset on another, the simultaneous binding of cursors in two volumes and the generation of a split pane image.
#### Intended Use:
Fusion7D registers pairs of anatomical and functional volumetric images (e.g. MRI-SPECT, MRI-PET, CT-SPECT, CT-PET), or pairs of anatomical volumetric images (e.g. MRI-MRI, CT-CT and MRI-CT) as a means to ease the comparison of image data. The result of the registration operation aims to help the clinician obtain a better understanding of the joint information that would otherwise have to be compared visually. This is useful for a wide range of clinical and therapeutic applications. It is important to note that the clinician retains the ultimate responsibility for making the pertinent diagnosis based on their standard procedures, including visual comparison of the separate unregistered images. Fusion7D is a complement to these standard procedures.
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# Predicate Devices:
| 510(k) No. | Tradename | Manufacturer | Component Applicable to |
|------------|------------------------------------|---------------------|----------------------------------------------------|
| K010336 | Advantage Windows CT/PET<br>Fusion | General<br>Electric | Anatomical to Functional<br>Registration Component |
| K983256 | Advantage Windows Fusion | General<br>Electric | Anatomical to Anatomical<br>Registration Component |
| K992654 | Plug 'n View 3D | Voxar | Visualization |
・
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# DEPARTMENT OF HEALTH & HUMAN SERVICES
Image /page/3/Picture/1 description: The image shows the logo for the U.S. Department of Health & Human Services. The logo features a stylized eagle with three stripes representing the department's mission. The text "DEPARTMENT OF HEALTH & HUMAN SERVICES - USA" is arranged in a circular pattern around the eagle. The logo is black and white and appears to be extracted from a document.
#### Public Health Service
Food and Drug Administration 9200 Corporate Boulevard Rockville MD 20850
# APR 2 6 2002
Mirada Solutions Ltd. % Mr. Roger W. Barnes Regulatory Consultant 342 Sunset Bay Road HOT SPRINGS AK 71913 Re: K020546
Trade/Device Name: Fusion 7D Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communication system
Regulatory Class: II Product Code: 90 LLZ Dated: February 7, 2002 Received: February 19, 2002
Dear Mr. Barnes:
We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820); and if applicable, the electronic product radiation control provisions (sections 531-542 of the Act); 21 CFR 1000-1050.
{4}------------------------------------------------
This letter will allow you to begin marketing your device as described in your 510(k) premarket notification. The FDA finding of substantial equivalence of your device to a legally marketed predicate device results in a classification for your device and thus, permits your device to proceed to the market.
If you desire specific advice for your device on our labeling regulation (21 CFR Part 801), please contact the Office of Compliance at one of the following numbers, based on the regulation number at the top of this letter:
| 8xx.1xxx | (301) 594-4591 |
|----------------------------------|----------------|
| 876.2xxx, 3xxx, 4xxx, 5xxx | (301) 594-4616 |
| 884.2xxx, 3xxx, 4xxx, 5xxx, 6xxx | (301) 594-4616 |
| 892.2xxx, 3xxx, 4xxx, 5xxx | (301) 594-4654 |
| Other | (301) 594-4692 |
Additionally, for questions on the promotion and advertising of your device, please contact the Office of Compliance at (301) 594-4639. Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). Other general information on your responsibilities under the Act may be obtained from the Division of Small Manufacturers, International and Consumer Assistance at its toll-free number (800) 638-2041 or (301) 443-6597 or at its Internet address http://www.fda.gov/cdrh/dsma/dsmamain.html.
Sincerely yours,
Nancy C. Brogdon
Nancy C. Brogdon Director, Division of Reproductive, Abdominal, and Radiological Devices Office of Device Evaluation Center for Devices and Radiological Health
Enclosure
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INDICATION FOR USE FORM
· Ver/ 3 - 4/24/96
Applicant: Mirada Solutions Ltd.
Ko20546 510(k) Number (if known):
Device Name: Fusion7D
Indications For Use:
Fusion7D registers pairs of anatomical and functional volumetric images (e.g. MRI-SPECT, MRI-PET, CT-SPECT, CT-PET), or pairs of anatomical volumetric images (e.g. MRI-MRI, CT-CT and MRI-CT) as a means to ease the comparison of image volume data by the clinician. The result of the registration operation aims to help the clinician obtain a better understanding of the joint information that would otherwise have to be compared visually. This is useful for a wide range of clinical and therapeutic applications. It is important to note that the clinician retains the ultimate responsibility for making the pertinent diagnosis based on their standard procedures including visual comparison of the separate unregistered images. Fusion7D is a complement to these standard procedures.
# (PLEASE DO NOT WRITE BELOW THIS LINE - CONTINUE ON ANOTHER PAGE IF NEEDED)
# Concurrence of CDRH, Office of Device Evaluation (ODE)
(Per 21 CFR 801.109) David L. Swann
(Optional Format 1-2-6)
Division Sign-Off)
Division of Reproductive, Abdominal,
and Radiological Devices
510(k) Number K020546
*Prescription Use*
Strictly Confidential ms387-0
Two short videos show you everything — or skip straight to the written tutorial if you'd rather read. You can reopen this any time from the Tutorial button in the top bar.
Part 1 — Search, results, and everyday workflows 16 min
Part 2 — Embeddings: the galaxy map 3 min
1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
Use the checkboxes above the results to narrow: SaMD keeps only software-only devices, AI / ML keeps only devices with AI.
Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
Where do you find a device's intended use without opening the PDF?
Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
4. Device detail page: chat and citations
Click a device name to open its detail page: device facts on the left, a chat window on the right. Ask something like "Describe the training data". The answer carries little citation bubbles — click one to jump to the highlighted passage in the source PDF, so you can verify every AI answer against the document. There's also a Download PDF button for sharing.
How do you verify an AI chat answer on the device detail page?
Click the citation bubbles to jump to the relevant highlight in the source document.
Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
5. Side-by-side comparison
Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
6. Collections
With rows selected, go to the Collections tab and create a labeled collection (e.g., "Cobb Angle Project"). Reload that selection any time — before a client call, pull up the collection and ask questions across all of its devices at once.
How do you save a set of selected devices for later use?
Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
7. Product codes and the regulations tree
Click a product code in the results to jump to it in the regulations tree — identification text, sibling product codes, and devices you can open in a PDF viewer on the right. Click a regulation number to see its identification, special controls, and related product codes. You can also search by product code or regulation number at the top of the tree. Always read the special controls if any exist for your device — it broadens your search and sharpens pre-kickoff research.
What can you do from the regulations tree view?
Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
8. Chart view
Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.
