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510(k) Data Aggregation

    K Number
    K033005
    Device Name
    MFGD 1318 18 INCH 1 MEGAPIXEL GREYSCALE LCD DISPLAY
    Manufacturer
    BARCO NV BARCOVIEW
    Date Cleared
    2004-04-19

    (207 days)

    Product Code
    LLZ
    Regulation Number
    892.2050
    Type
    Traditional
    Panel
    Radiology
    Reference & Predicate Devices
    K023340
    Why did this record match?
    Device Name :

    MFGD 1318 18 INCH 1 MEGAPIXEL GREYSCALE LCD DISPLAY

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The MFGD 1318 18 Inch 1 Megapixel Grayscale LCD Display is intended to be used as a tool in displaying and viewing digital images (excluding digital mammography) for review and analysis by trained medical practitioners.

    Device Description

    The MFGD 1318 is a diagnostic display. The MFGD 1318 device is a high resolution monitor with electronic capabilities for evaluation of high resolution medical images.

    AI/ML Overview

    This 510(k) premarket notification (K033005) is for a medical display device, not an AI/ML algorithm. Therefore, many of the requested categories related to AI/ML software performance (like sample sizes for test/training sets, expert ground truth, adjudication methods, MRMC studies, or standalone algorithm performance) are not applicable.

    The submission focuses on establishing substantial equivalence to a predicate device (Coronis 1MP Medical Flat Panel Display System, K023340) based on technological characteristics and intended use. The "acceptance criteria" here refer to the performance specifications of the display hardware, and "study" refers to tests and comparisons demonstrating these specifications are met and are equivalent to the predicate.

    Here's the information that can be extracted, and where the requested AI/ML specific information is not applicable (N/A):

    1. Table of acceptance criteria and the reported device performance
    CriteriaMFGD 1318 PerformanceBasis for Acceptance
    Intended UseDisplaying and viewing digital images (excluding digital mammography) for review by trained medical practitioners.Substantially equivalent to predicate device (K023340) which has the same intended use for medical practitioners.
    Technological CharacteristicsHigh resolution monitor with electronic capabilities for evaluation of high resolution medical images.Substantially equivalent to predicate device (K023340) as both are 1 Megapixel Grayscale LCD Displays for medical imaging. Specific technical display parameters (resolution, brightness, contrast, etc.) would have been detailed in the full 510(k) submission, but are not provided in this summary.
    Display Type18 Inch 1 Megapixel Grayscale LCD DisplayMatches the display type and resolution category of the predicate device.

    1. Sample size used for the test set and the data provenance

      • Sample size for test set: N/A (as this is a hardware device, not an AI/ML algorithm evaluated on a dataset of medical images).
      • Data provenance: N/A

    2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

      • N/A (no ground truth established in the context of an AI/ML algorithm's performance on medical images).

    3. Adjudication method for the test set

      • N/A

    4. 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

      • N/A (This is not an AI-assisted device). The evaluation here is about the technical performance of a display, not its impact on human reader performance with AI.

    5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

      • N/A (This is a display device, not a standalone algorithm).

    6. The type of ground truth used

      • N/A. The "ground truth" for a display device would relate to its physical characteristics meeting industry standards and safety regulations, not a medical diagnosis dataset.

    7. The sample size for the training set

      • N/A.

    8. How the ground truth for the training set was established

      • N/A.
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