(135 days)
The Coronis 5MP Medical Flat Panel Display System is intended to be used in displaying and viewing digital images, including digital mammography, for review by trained medical practitioners.
The Coronis 5MP Medical Flat Panel Display System is intended to be used as a tool in displaying and viewing digital images, including digital mammography, for review and analysis by trained medical practitioners.
The Coronis 5MP device is a digital image display system
The Coronis 5MP device consists of components to provide high resolution visualization of digital images.
This document is a 510(k) summary for the Barco Coronis 5MP Medical Flat Panel Display System, a digital image display system intended for viewing digital images, including digital mammography.
1. Table of Acceptance Criteria and the Reported Device Performance:
The provided document does not contain a table of acceptance criteria or reported device performance in the typical sense of quantitative metrics for an AI device. Instead, it describes a medical device (a display system) and seeks substantial equivalence to existing devices. The "performance" being assessed here is the device's ability to display images adequately for medical review, and the acceptance is based on meeting the regulatory requirements for such a display system.
However, based on the context of a 510(k) for a display system, the implicit acceptance criteria would revolve around the display's ability to accurately and sufficiently present medical images, particularly for mammography. This would typically involve:
| Acceptance Criteria (Implied for a Medical Display) | Reported Device Performance (Implied from Substantial Equivalence Claim) |
|---|---|
| Resolution (e.g., 5 Megapixels) | Coronis 5MP (implies meeting 5 Megapixel performance) |
| Brightness/Luminance | Comparable to predicate devices (K013922, K040443) |
| Contrast Ratio | Comparable to predicate devices (K013922, K040443) |
| Uniformity | Comparable to predicate devices (K013922, K040443) |
| DICOM compliance | Implicit for a medical display system |
| Intended Use (displaying digital images including mammography for trained practitioners) | Device is marketed for this explicit intended use. |
2. Sample size used for the test set and the data provenance:
- No specific test set or data provenance is mentioned. This document is a regulatory submission for a display device, not a study evaluating an AI algorithm's diagnostic performance on a dataset of patient images. The evaluation is focused on the characteristics of the display itself and its equivalence to other legally marketed predicate devices.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Not applicable. As this is a display device, there's no "ground truth" establishment in the context of diagnosing cases. The evaluation focuses on technical specifications of the display and its suitability for medical image review.
4. Adjudication method for the test set:
- Not applicable. No test set requiring expert adjudication is mentioned for this device.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:
- Not applicable. This document pertains to a medical display system, not an AI algorithm. Therefore, an MRMC study comparing human readers with and without AI assistance is not relevant or mentioned.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- Not applicable. The device is a display system, not an algorithm.
7. The type of ground truth used:
- Not applicable. No ground truth in the context of diagnostic accuracy is used for evaluating this display system. The "ground truth" for a display would refer to objective technical specifications and performance against industry standards.
8. The sample size for the training set:
- Not applicable. This document does not describe the development or training of an AI algorithm.
9. How the ground truth for the training set was established:
- Not applicable. This document does not describe the development or training of an AI algorithm.
§ 892.2050 Medical image management and processing system.
(a)
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.(b)
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).