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The use of DownScan LT is indicated whenever the source and destination of a video signal are incompatible due to different line rates or other signal attributes, and a standard frame rate video signal (30 or 25 frames/second) is required. Examples include conversion of X-ray (stationary, C-arm, angiography, etc.), nuclear medicine, magnetic resonance, and ultrasound images either directly from their source, or from an intermediate storage device (like a video tape or video disk), for use on display monitors, optical, tape, or disk recorders, or other apparatus requiring a standard frame rate signal.

DownScan LT is a digital image processing system that can convert from high line rate video standard of 1023-1125/60 or 1249/50 to low line rate video standards of 525/30 or 625/25. Housed in a 1 3/4" EIA half-rack mount chassis, DownScan LT operates from 100V to 240V AC power.

This document describes the Merlin DownScan LT, a digital image processing system designed to convert high line rate video to low line rate video. It serves as a regulatory submission (510(k)) to the FDA, demonstrating substantial equivalence to predicate devices.

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size Used for the Test Set and Data Provenance

The document does not specify a distinct "test set" with a dedicated sample size in the conventional sense of a clinical or image-based study. The performance tests described are related to engineering and signal processing standards. The data provenance is not explicitly stated as retrospective or prospective, but the tests were conducted by the manufacturer, Merlin Engineering Works, to demonstrate compliance with industry standards. The country of origin for the device's testing and manufacturer is the USA.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

This information is not provided. The "ground truth" for the tests appears to be defined by established industry technical standards (RS-170, RS-343A, SMPTE RP-133) rather than expert consensus on medical images.

4. Adjudication Method for the Test Set

This information is not provided. Given the nature of the tests (compliance with technical specifications), it is likely that measurements and comparisons to defined standards were performed, rather than an adjudication process involving human interpretation of medical images.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done for this device. The document describes a video signal processing system, not a diagnostic imaging aid that would typically involve human readers.

6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) Was Done

Yes, the performance tests described are inherently standalone in the sense that they evaluate the device's adherence to technical standards and objective performance metrics (e.g., aspect ratio compensation, low-contrast resolution) without human intervention in the primary function or assessment. The device's role is to convert video signals, not to interpret medical images.

7. The Type of Ground Truth Used

The ground truth used for these tests is based on established technical standards and specifications:

• RS-170 (a standard for monochrome video signals)
• RS-343A (another standard for monochrome video signals, often related to higher resolution)
• SMPTE RP-133 (a recommended practice by the Society of Motion Picture and Television Engineers, likely related to image quality and display characteristics for medical imaging).
  The performance criteria are objective measurements against these predefined benchmarks.

8. The Sample Size for the Training Set

This information is not applicable and not provided. The DownScan LT is a digital image processing system that converts video signals. It is not an AI/ML algorithm that requires a "training set" in the typical sense for learning patterns from data. Its function is based on engineered signal processing algorithms, not learned models.

9. How the Ground Truth for the Training Set Was Established

This information is not applicable, as there is no "training set" for this type of device. The device's operation is based on predefined signal processing logic and hardware, not on machine learning from a dataset with established ground truth.

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