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The indications for use of the Fuji Medical Dry Imagers is the production of hard copy images from medical image data.

The device accepts electrical image signals and produces hard copy images signal source may be digital formatted image data from Fuji Computed Radiography image readers in the case of the FM-DP 2636CR, or unformatted image data from other imaging modalities (e.g. CT, MRI) in the case of the FM-DP 2636. The image signal source of for the FM-DP 2636 may be analog or digital.

The Fuji Medical Dry Imager uses the information in the image signals to control discrete elements in a linear thermal head which writes on the translating Fuji Medical Dry Imaging Film DI-AT, a thermal recording media. Unlike conventional laser imagers and multiformat cameras, there is no laser, cathode ray tube, or optics. Unlike conventional light-sensitive silver halide photographic media, the film requires no dark room, film processor, processing chemicals, water, drainage, or dryer ventilation, produces no chemical waste, and requires no space for chemical storage.

The major components of the imager are the film magazine, transport mechanics, imaging electronics, and thermal head.

The provided text describes a 510(k) summary for a medical image printer, not a device that utilizes AI or machine learning. Therefore, many of the requested categories related to AI performance, ground truth, and expert evaluation are not applicable.

Here's the information that can be extracted or deduced from the provided text:

Acceptance Criteria and Device Performance

The acceptance criteria are implicitly defined by comparison to the predicate device, the Fuji Medical Laser Imager Fuji FL-IM D. The goal is to demonstrate "similar" or "judged adequate" performance for medical image hard copy devices, specifically focusing on:

Study Details

The document describes a comparison study where the performance of the new device is compared against a predicate device. It is not a clinical study involving patients or diagnosticians interpreting images.

1. Sample size used for the test set and the data provenance: Not applicable. This is a technical performance comparison of imaging hardware, not a diagnostic test. The "test set" would be the output images generated by the devices, likely using standardized test patterns and medical image data. The provenance of this data is not specified beyond "medical image data".
2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. The "ground truth" here is objective technical performance metrics (spatial resolution, gray scale, density uniformity), not diagnostic accuracy requiring expert interpretation.
3. Adjudication method for the test set: Not applicable. Performance is measured objectively.
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: No, an MRMC study was not done. This device is an image printer, not an AI-powered diagnostic tool.
5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Yes, in essence, the study evaluates the standalone technical performance of the imaging device. There is no "human-in-the-loop" component in the performance evaluation described.
6. The type of ground truth used: Technical specifications and measurements. For example, spatial density is measured in pixels/mm, square wave response is a quantitative value, and gray scale resolution is expressed in bits. Density uniformity is measured by Wiener Spectrum values. These are objective engineering and imaging science metrics.
7. The sample size for the training set: Not applicable. There is no machine learning or AI involved; thus, no training set is relevant.
8. How the ground truth for the training set was established: Not applicable, as there is no training set.

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