Subtle Medical, Inc.

Gajanana Keshava Datta

Enhao Gong

Ben Andrew Duffy

David Van Veen

Provided herein are methods for automated image quality control (QC). The method comprises: generating training data based at least in part on metadata obtained from a data augmentation process; training a model for a QC task based at least in part on the training data. The model is trained using a self-supervised learning algorithm.

Self-supervised learning for medical image quality control

A computer-implemented method is provided for improving live video quality. The method comprises: (a) acquiring, using a medical imaging apparatus, a stream of consecutive image frames of a subject; (b) feeding the stream of consecutive image frames to a first set of denoising components, wherein each of the first set of denoising components is configured to denoise an image frame from the stream of consecutive image frames in a spatial domain to output an intermediate image frame; (c) feeding a plurality of the intermediate image frames to a second denoising component, wherein the second denoising component is configured to (i) denoise the plurality of the intermediate image frames in a temporal domain and (ii) generate a weight map; and outputting a final image frame with improved quality in both temporal domain and spatial domain based at least in part on the weight map.

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Los Altos, CA, United States of America

Gajanana Keshava Datta