(80 days)
The Barco Coronis 2MP Medical Flat Panel Display System is intended to be used in displaying and viewing digital images for review by trained medical practitioners.
The Coronis 2MP Medical Flat Panel Display System is intended to be used in displaying and viewing digital images for review and analysis by trained medical practitioners.
The Coronis 2MP device is a digital image display system
The Barco Coronis 2MP device consists of components to provide high resolution visualization of digital images.
The provided text is a 510(k) summary for the Barco Coronis 2MP Medical Flat Panel Display System, which is an image display system. The document does not contain specific acceptance criteria, performance data, or details of a study that proves the device meets acceptance criteria in the way typically expected for an AI/algorithm-based medical device.
This document describes a medical display system (hardware), not an AI algorithm. Therefore, many of the requested elements (like sample sizes for test/training sets, expert qualifications for ground truth, MRMC studies, standalone algorithm performance, and ground truth establishment) are not applicable or would not be found in such a submission for a display device.
However, I can extract the information that is present and indicate where the requested information is not available:
1. A table of acceptance criteria and the reported device performance
The submission acts as a declaration that the Barco Coronis 2MP Medical Flat Panel Display System is "substantially equivalent" to a legally marketed predicate device (Barco NV Display Systems Coronis 3MP Medical Flat Panel Display System (K013922)). For a display system, acceptance criteria are generally related to display characteristics (resolution, brightness, contrast, uniformity, viewing angle, stability, calibration capabilities, etc.) and compliance with relevant medical display standards (e.g., DICOM Part 14, AAPM TG18). These specific technical performance metrics are not detailed in the provided 510(k) summary. The summary focuses on the device's intended use and classification.
The "reported device performance" is implicitly that it meets the requirements for substantial equivalence to the predicate device for displaying and viewing digital images for review by trained medical practitioners. Specific numerical performance values are not provided in this summary.
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
Not applicable. This is a display system, not an algorithm being tested on a clinical image dataset.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)
Not applicable. This is a display system. "Ground truth" in the context of image interpretation by experts is not relevant here.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable.
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 is a display system, and it is not an AI-assisted device.
6. If a standalone (i.e. algorithm only, without human-in-the-loop performance) was done
Not applicable. This is a display system, not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
Not applicable.
8. The sample size for the training set
Not applicable. This is a display system, not an algorithm that undergoes training.
9. How the ground truth for the training set was established
Not applicable.
§ 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).