SwiftMR is a software device that automatically enhances MRI images by reducing noise and increasing image sharpness using deep learning algorithms. It supports brain, spine, and musculoskeletal MRI images and integrates with existing PACS systems to improve diagnostic image quality without interrupting clinical workflow.
SwiftMR is a stand-alone software solution intended to be used for acceptance, enhancement and transfer of brain, spine, knee, ankle, shoulder and hip MR images in DICOM format. It can be used for noise reduction and increasing image sharpness for non-contrast enhanced MR images.
SwiftMR is a software as a medical device (SaMD) that applies deep learning algorithms and sharpening filters to enhance MR images in DICOM format. It runs in the background, automatically receiving MR images, performing denoising and sharpening (sharpness level adjustable from 0 to 5), and transferring enhanced images back to PACS. It supports multiple pulse sequences with four dedicated deep learning models.
Performance testing included unit, integration/system testing, and validation using retrospective clinical MRI images from multiple manufacturers and field strengths. The device demonstrated a signal-to-noise ratio increase of 40% or more and a sharpness increase meeting preset criteria across various anatomical regions, showing substantial equivalence to the predicate device.
No predicate devices specified
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