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The CareView 1500C/ CareView 1500L detector is indicated for digital imaging solution designed for providing general radiographic diagnosis of human anatomy. It is intended to replace radiographic film/screen systems in all general-purpose diagnostic procedures. This product is not intended for mammography applications.

CareView 1500C/ CareView 1500L is a kind of cassette size digital X-ray flat panel detectors which have 434mmx355mm imaging area. The device communicates by wired communication feature (Giga-bit Ethernet communication mode by connecting the power box).

The device intercepts X-ray photons and then the scintillator emits visible spectrum photons that illuminate an array of photo detectors (a-Si) that create electrical signals. After the electrical signals are generated, it is converted to a digital value and an image will be displayed on the monitor.

The detector should be integrated with an operating PC and an X-ray generator to utilize as digitalizing X-ray images and transfer for radiography diagnostic.

The provided document is a 510(k) summary for the CareView 1500C/CareView 1500L X-ray Flat Panel Detectors. It focuses on demonstrating substantial equivalence to a predicate device (CareView 1500Cw) rather than outlining specific acceptance criteria for algorithm performance and a study proving it meets those criteria.

This document describes a medical device (an X-ray flat panel detector) and its physical and performance specifications, but it does not involve an AI algorithm with specific acceptance criteria that require a test set, ground truth, or expert review. Therefore, I cannot provide the requested information regarding the acceptance criteria for an AI device, the study proving it meets those criteria, sample sizes for test and training sets, expert adjudication, or MRMC studies.

The closest information provided in the document related to "performance" is in the "Technological Characteristics" table on page 6, which compares the proposed device's specifications to those of the predicate device. These are hardware specifications, not AI algorithm performance metrics.

For example, the document states:

• Image Matrix Size: 2304 x 2816 pixels for both proposed and predicate devices.
• Pixel Pitch: 154µm for both.
• Effective Imaging Area: 355 mm x 434 mm for both.
• Grayscale: 16 bit, 65536 grayscale for both.
• Spatial Resolution: Min. 3.3 line pair/mm for both.

These are engineering specifications of the X-ray detector itself, not acceptance criteria for an AI algorithm's diagnostic performance. The document's conclusion (page 9) explicitly states that differences in connectivity and power supply "do not raise any new questions of safety and effectiveness," implying that the device's imaging performance is considered equivalent to the predicate without needing new clinical performance studies.

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