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21.3 inch (53cm) Monochrome Digital Mammography 5M pixel LCD Monitor with subpixel driving techniques enabling 15M subpixels to be driven independently. MS51i2 (MDL2123A) is intended to be used in displaying and viewing medical images for diagnosis by trained medical practitioners. It is to be used in digital mammography PACS and modalities including FFDM.

MS51i2 (MDL2123A) is a 21.3-inch (53 cm) monochrome LCD monitor whose display resolution is 2048 x 7680 (landscape), 7680 x 2048 (portrait) supporting DVI (digital visual interface).

The provided text is a 510(k) summary for a medical display monitor (TOTOKU ELECTRIC CO., LTD. MS51i2). It describes the device, its intended use, and substantial equivalence to a predicate device. However, it does not contain information about acceptance criteria or a study proving the device meets performance criteria in the way that would be expected for an AI/CADe device.

This document is a regulatory submission for a display monitor, which is a hardware component. Its performance is assessed differently than a software algorithm that performs analysis or detection. The key aspects of this submission revolve around demonstrating that the new monitor is substantially equivalent to an existing, legally marketed monitor, primarily focusing on hardware specifications and intended use.

Therefore, I cannot fulfill the request to provide a table of acceptance criteria and reported device performance from this document, nor can I provide information on various study design elements (sample size, experts, adjudication, MRMC, standalone performance, ground truth, training set specifics) because these types of studies are not typically conducted or described for a display monitor's 510(k) submission.

The 510(k) process for this device focuses on demonstrating that the monitor performs as expected for displaying medical images, not on its ability to interpret or detect findings. The acceptance criteria for such a device would likely pertain to display characteristics (resolution, brightness, contrast, color accuracy, uniformity), and testing would involve measurements against established standards (e.g., DICOM Part 14 calibration). This document does not detail those specific acceptance criteria or performance test results.

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20.1-inch (51cm) Color LCD Monitor CDL2009A (CCL204) is to be used in displaying and viewing medical images for diagnosis by trained medical practitioners. It is not meant to be used for digital mammography.

CDL2009A has a multi-displaying function corresponding to the resolution from VGA 640 x 480 to UXGA 1600 x 1200. This is also compliant with VESA standard display mode.

This document describes the 510(k) premarket notification for the TOTOKU 20.1-inch (51cm) Color LCD Monitor CDL2009A (CCL204). It is important to note that this is a submission for a display device, not an Artificial Intelligence (AI) enabled device. Therefore, many of the requested categories related to AI performance, ground truth, and expert evaluation are not applicable.

Here's an analysis of the provided information:

1. A table of acceptance criteria and the reported device performance

For a medical display device, acceptance criteria typically revolve around image quality, luminance, uniformity, resolution, and adherence to display standards for diagnostic viewing. The provided document, being a 510(k) summary, does not detail specific acceptance criteria values or a direct side-by-side comparison with reported performance. Instead, it focuses on demonstrating substantial equivalence to a predicate device.

However, based on the nature of the device (a color LCD monitor for medical image display), the following are implied or commonly expected performance aspects for such a device. The "Reported Device Performance" column indicates what the summary states about the device's capabilities, rather than specific measured values against a numerical criterion.

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

For a medical display device, there isn't typically a "test set" of images in the same way an AI algorithm is tested. Instead, performance testing involves:

• Physical measurements: Using calibration tools and specialized equipment to measure luminance, contrast, uniformity, resolution, color accuracy, and other display characteristics.
• Observer studies (human factors): In some cases, human observers (e.g., radiologists) might evaluate the display for ergonomic factors, clarity, and image quality, though this is less common for substantial equivalence submissions for monitors if the technical specifications are benchmarked.

The provided 510(k) summary does not specify a sample size for image quality evaluation (as it's not an AI model). The evaluation of the device features and performance would have been based on technical specifications, engineering tests, and possibly human factors evaluations against predefined technical standards and predicate device performance.

Data provenance: Not applicable in the context of image data for an AI model. The "data" here refers to the device's technical specifications and measurement results.

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

Not applicable. "Ground truth" for a display device is established by objective, measurable technical specifications and industry standards for display performance (e.g., luminance, contrast ratios, color gamut). It does not involve expert medical readers establishing ground truth on cases.

4. Adjudication method for the test set

Not applicable. There is no "test set" of medical cases requiring adjudication for a display 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 is a display device, not an AI-enabled system or a diagnostic tool that assists human readers.

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

Not applicable. This is a display device, not an algorithm.

7. The type of ground truth used

The "ground truth" for a medical display is its physical and optical performance characteristics measured against established industry standards (e.g., DICOM Part 14 for grayscale, various color calibration standards, VESA display modes) and the specifications of an identified predicate device. These are objective engineering measurements rather than subjective expert consensus or pathology results.

8. The sample size for the training set

Not applicable. This is a hardware device, not an AI model. There is no "training set" in this context.

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

Not applicable. There is no "training set" or "ground truth for a training set" for this device.

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