ZOOM Image Enhancement System is an image processing software that can be used for image enhancement in MRI images. Enhanced images will be sent to PACS server and exist in conjunction to the original images.
Device Story
ZOOM is an image processing software for MRI enhancement; operates on a remote computer. Inputs: DICOM images from MRI host computer. Processing: noise reduction via wavelet decomposition, soft thresholding of wavelet sub-bands, and inverse wavelet transform reconstruction. Outputs: enhanced DICOM images sent to PACS server. Workflow: automated processing of received images; enhanced images stored alongside originals. Benefits: improves signal-to-noise ratio (SNR) by at least 10% without degrading contrast resolution, aiding clinical image quality.
Clinical Evidence
Bench testing only. Validation performed using 64 data sets acquired via ACR MRI phantom on GE 1.5T Excite, Siemens Avanto 1.5T, Philips Intera 1.5T, and Toshiba Titan 1.5T systems. Sequences included spin echo, fast spin echo, and gradient echo. Primary endpoint: SNR improvement of at least 10% in slice 7 of ACR phantom data without degrading high-contrast (slice 1) or low-contrast (slice 11) resolution. All tests passed.
Technological Characteristics
Software-based image enhancement. Operates on PC/PC-compatible hardware (Intel i3, 4GB RAM, 500GB HDD). OS: Windows 7. Input/Output: DICOM. Algorithm: Wavelet-based noise reduction with image-guided filtering. Connectivity: Networked (receives from MRI host, sends to PACS).
Indications for Use
Indicated for image enhancement of MRI images. No specific patient population, age, or gender restrictions are defined.
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).
Predicate Devices
Context Vision Sharp View Image Enhancement System (K024028)
Submission Summary (Full Text)
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Zetta Medical Technologies, LLC. Main Ghazal President 1313 Ensell Road LAKE ZURICH IL 60047
April 24, 2018
Re: K172768
Trade/Device Name: ZOOM Regulation Number: 21 CFR 892.2050 Regulation Name: Picture Archiving and Communications System Regulatory Class: Class II Product Code: LLZ Dated: March 14, 2018 Received: March 23, 2018
Dear Main Ghazal:
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 of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
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); medical device reporting (reporting of medical device-related adverse events) (21 CFR 803); good manufacturing practice requirements as set forth in the quality systems (OS) regulation (21 CFR Part 820); and if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
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Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to http://www.fda.gov/MedicalDevices/Safety/ReportaProblem/default.htm for the CDRHs Office of Surveillance and Biometrics/Division of Postmarket Surveillance.
For comprehensive regulatory information about medical devices and radiation-emitting products, including information regulations, please Device about labeling see Advice (https://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/) and CDRH Learn (http://www.fda.gov/Training/CDRHLearn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (http://www.fda.gov/DICE) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely,
Michael D. O'Hara For
Robert A. Ochs, Ph.D. Director Division of Radiological Health Office of In Vitro Diagnostics and Radiological Health Center for Devices and Radiological Health
Enclosure
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# Indications for Use
510(k) Number (if known) K172768
Device Name ZOOM
Indications for Use (Describe)
ZOOM Image Enhancement System is an image processing software that can be used for image enhancement in MRI images. Enhanced images will be sent to PACS server and exist in conjunction to the original images.
Type of Use (Select one or both, as applicable)
| <div> <span> <span style="font-size:16px">☑</span> Prescription Use (Part 21 CFR 801 Subpart D) </span> </div> |
|--------------------------------------------------------------------------------------------------------------------|
| <div> <span> <span style="font-size:16px">☐</span> Over-The-Counter Use (21 CFR 801 Subpart C) </span> </div> |
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# 510(k) Summary of Safety and Effectiveness
This 510(k) summary of safety and effectiveness is being submitted in accordance with the requirement of Titles 21 CFR §807.87 and 807.92.
- 1. Applicant & Submitted By: Zetta Medical Technologies, LLC. 1313 Ensell Road, Lake Zurich, IL 60047 Phone: (847) 550-9990 Fax: (847) 550-9994 Contact Person: Main M. Ghazal, President Date Prepared: March 14th 2018
#### 2. Identification of the Device:
Trade Name: ZOOM Common Name: Image Enhancement System Classification Name: Image Processing System, Radiological (21 CFR, 892.2050, LLZ) Regulatory Description: Picture Archiving and Communications System
### 3. Predicate Device:
Context Vision Sharp View Image Enhancement System, K024028
### 4. Indications for Use:
ZOOM Image Enhancement System is an image processing software that can be used for image enhancement in MRI images. Enhanced images will be sent to PACS server and exist in conjunction to the original images.
### 5. Device Description:
ZOOM Image Enhancement System is an image processing software that can be used for image enhancement in MRI images. ZOOM image enhancement software implements a noise reduction algorithm using wavelets and image guided filtering. Original images are decomposed into different wavelet sub bands and noise in each band is soft threshold. De-noised images are reconstructed from softthresholded images using inverse wavelet transform. The software, which is installed on a remote computer, receives DICOM images from MRI host computer, automatically processes the received images and sends the enhanced images to a PACS server. Enhanced images exist in conjunction to the original images.
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# 6. Substantial Equivalence Table
The subject device ZOOM is substantially equivalent to the predicate device, Sharp View Image Enhancement System. The main difference is that Sharp View Enhancement Image transfer/storage/enhancement system where as ZOOM (as of 7/27/2017) is strictly an MRI image enhancement software. Detailed differences between ZOOM and Sharp view systems are listed in Table-1.
| Characteristics | ZOOM | Sharp View Image<br>Enhancement System |
|------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Indications for<br>Use | ZOOM Image<br>Enhancement System is<br>an image processing<br>software that can be used<br>for image enhancement<br>in MRI images.<br>Enhanced images will be<br>sent to PACS server and<br>exist in conjunction to<br>the original images. | The Image Enhancement<br>System is intended for use by<br>a qualified/trained<br>technologist for transfer,<br>storage, enhancement and<br>viewing of multi-modality<br>images. |
| Computer | PC or PC Compatible | PC compatible |
| Operating<br>System | Windows 7 | Windows 98, NT 4.0, 2000 and<br>XP |
| Storage | Is not a primary image<br>storage system.<br>However, processed<br>images are archived on<br>local hard drive | Hard disk or any compatible<br>PC method: Optical, CDROM,<br>Tape |
| Image Processing<br>Hardware | Intel i3 processor, 4GB<br>RAM, 500GB Hard drive | Javelin (PCI-bus) or Similar |
| Software core | ZOOM Image<br>Enhancement Software<br>(Zetta's own trademark) | GOP® Enhancement software<br>(The GOP trademark is the<br>property of Context Vision) |
| Image Input | DICOM | DICOM |
| Image output | DICOM | DICOM |
Table -1: ZOOM vs Sharp View Image Enhancement System
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## 7. Performance Testing:
ZOOM has been designed, verified and validated in compliance with FDA 21 CFR Part 820 requirements. The device has been validated through the use of ACR MRI PHANTOM. A total of 64 data sets were acquired using spin echo, fast spin echo and gradient echo based sequences from the following systems: GE 1.5T Excite, Siemens Avanto 1.5T, Philips Intera 1.5T and Toshiba Titan 1.5T. Parameters (slice thickness, field of view, matrix dimensions and number of averages) that effect the signal to noise ratio (SNR) were varied while acquiring the 64 data sets. These data sets were processed using ZOOM software for image enhancement and results are compared between original and processed images. Performance test results indicate that the ZOOM software improves SNR by at least 10% without degrading high and low contrast resolutions.
| Requirement specification | Verified on systems | Result |
|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------|--------|
| For spin echo large phantom protocol in<br>ACR quality control 2015, the software<br>shall increase SNR by at-least 10% in slice<br>7 ACR data without compromising high<br>contrast resolution in slice 1 and low<br>contrast resolution in slice 11 | GE 1.5T Excite Siemens Avanto 1.5T Philips Intera 1.5T Toshiba Titan 1.5T | Pass |
| For fast spin echo sequences with slice<br>thickness in the range 2-5mm and in-<br>plane resolution in the range 0.6-1.4 mm,<br>the software shall increase SNR by at-least<br>10% in slice 7 ACR data without<br>compromising high contrast resolution in<br>slice 1 and low contrast resolution in slice<br>11 | GE 1.5T Excite Siemens Avanto 1.5T Philips Intera 1.5T Toshiba Titan 1.5T | Pass |
| For gradient echo sequences with slice<br>thickness in the range 2-5mm and in-<br>plane resolution in the range 0.6-1.4 mm,<br>the software shall increase SNR by at-least<br>10% in slice 7 ACR data without<br>compromising high contrast resolution in<br>slice 1 and low contrast resolution in slice<br>11 | GE 1.5T Excite Siemens Avanto 1.5T Philips Intera 1.5T Toshiba Titan 1.5T | Pass |
| For spin echo small phantom protocol in<br>ACR quality control 2015, the software<br>shall increase SNR by at-least 10% in slice<br>7 ACR data without compromising high | GE 1.5T Excite Siemens Avanto 1.5T Philips Intera 1.5T Toshiba Titan 1.5T | Pass |
Table - 2: High level performance test results
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| contrast resolution in slice 1 and low |
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| contrast resolution in slice 11 |
#### 8. Safety and Effectiveness:
Based on the ZOOM software performance test results and incorporated risk minimization methods in design, Zetta Medical Technologies concludes that this device is substantially equivalent to the predicate device.
#### 9. Conclusion:
ZOOM is an image enhancement software which has similar indications for use as predicate device. The main difference is that the predicate device is a multimodality image transfer/storage/enhancement system where as ZOOM (as of 7/27/2017) is strictly an MRI image enhancement system. Performance test results and incorporated risk minimization methods demonstrate that ZOOM is as safe and effective as predicate device.
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.