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Lux HD 35 Detector and Lux HD 43 Detector are indicated for digital imaging solutions designed to provide general radiographic diagnosis for human anatomy including both adult and pediatric patients. They are intended to replace film/screen systems in all general-purpose diagnostic procedures. Lux HD 35 Detector and Lux HD 43 Detector are not intended for mammography or dental applications.

Lux HD 35 Detector and Lux HD 43 Detector are digital flat panel detector. They support the single frame mode, with the key component of TFT/PD image sensor flat panel of active area: 35cm×43cm (Lux HD 35 Detector)/42.67cm × 42.67cm (Lux HD 43 Detector) .The differences between two models are overall change in the dimensions of the image receptor. The sensor plate of Lux HD 35 Detector and Lux HD 43 Detector is direct-deposited with CsI scintillator to achieve the conversion from X-ray to visible photon. The visible photons are transformed to electron signals by diode capacitor array within TFT panel, which are composed and processed by connecting to scanning and readout electronics, consequently to form a panel image by transmitting to PC through the user interface. The major function of the Lux HD 35 Detector and Lux HD 43 Detector is to convert the X-ray to digital image, with the application of high resolution X-ray imaging. Both kinds of detectors are the key component of DR system. The Digital Radiographic Imaging Acquisition Software Platform - DR is part of the system, it is used to acquire, enhance, view image from Lux HD 35 Detector and Lux HD 43 Detector.

The provided text is a 510(k) summary for a medical device (Lux HD 35 Detector and Lux HD 43 Detector). It details the device's characteristics, intended use, and comparison to a predicate device to demonstrate substantial equivalence.

However, the provided document does not contain information about the acceptance criteria nor a study that proves the device meets specific performance criteria through a clinical evaluation involving human readers, ground truth establishment, or sample sizes related to AI/algorithm performance.

The "Non-clinical study" section primarily discusses:

• Electrical Safety and EMC testing: Adherence to IEC/ES 60601-1 and IEC 60601-1-2.
• Biological Evaluation: Evaluation of materials contacting operators/patients based on FDA guidance.
• Non-clinical Considerations: Stating substantial equivalence to the predicate device for non-clinical aspects mentioned in FDA guidance for solid-state X-ray imaging devices.
• Clinical Consideration: Stating that intended use, fundamental scientific technology, regulatory requirements, non-clinical performance, labeling, and quality-assurance programs are the same as the predicate device. It explicitly mentions: "There is no any negative change about clinical performance from predicate device."
• Wireless testing: Compliance with ANSI IEEE C63.27-2017.
• Cybersecurity testing: Compliance with section 524B(b)(2) of the Federal Food, Drug, and Cosmetics Act.

This submission clearly relies on demonstrating substantial equivalence to a predicate device (Carestream Health, Inc. Focus HD 43 Detector, K213529) through technical and safety comparisons, rather than presenting a performance study with acceptance criteria and results for an AI/algorithm.

Therefore, I cannot populate the table or answer the specific questions about "acceptance criteria and the study that proves the device meets the acceptance criteria" as they pertain to AI/algorithm performance, ground truth, expert adjudication, or MRMC studies. The document does not describe such a study.

The crucial information regarding acceptance criteria and performance data for an AI/algorithm, as requested in your prompt, is absent from the provided text. The document is a 510(k) a summary for a hardware device (X-ray detector) and focuses on the safety and performance equivalency to a predicate hardware device. It does not provide data on AI/algorithm performance against a clinical ground truth.

If this device were to include an AI component that required such a study for its clearance, that information would typically be detailed in a separate section of the 510(k) submission, outlining the AI's intended use, performance metrics, validation strategy, and results against a defined ground truth. This document does not contain that.

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