Self-Supervised Ultrasound Screen Detection
By: Alberto Gomez , Jorge Oliveira , Ramon Casero and more
Potential Business Impact:
Turns ultrasound photos into usable computer images.
Ultrasound (US) machines display images on a built-in monitor, but routine transfer to hospital systems relies on DICOM. We propose a self-supervised pipeline to extract the US image from a photograph of the monitor. This removes the DICOM bottleneck and enables rapid testing and prototyping of new algorithms. In a proof-of-concept study, the rectified images retained enough visual fidelity to classify cardiac views with a balanced accuracy of 0.79 with respect to the native DICOMs.
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