Combined compression and feature extraction models for storing and analyzing medical videos

A system comprising:

• a memory configured to store a plurality of processor-executable instructions, the memory including:
• a video compressor based on a first pretrained machine learning model;
• a target feature detector based on a second pretrained machine learning model;
• and,
• a processor configured to execute the plurality of processor-executable instructions instruction to perform operations including:
• receiving an uncompressed medical video comprising at least one target feature;
• compressing the uncompressed medical video to generate a compressed medical video based on a predicted location of the at least one target feature;
• and,
• detecting a location of the at least one target feature of the compressed medical video,
• wherein the first pretrained machine learning model and the second pretrained machine learning model are trained in tandem using domain-specific medical videos in a manner that, in a first iteration, a training medical video is both compressed and analyzed to detect a location of at least one training target feature before a start of a second iteration after the first iteration, and
• wherein the first pretrained machine learning model is trained to compress a first video frame differently from a second video frame, the first video frame comprising the location of at least one training target feature and the second video frame not comprising the location of at least one training target feature.

A non-transitory processor-readable storage medium storing a plurality of processor-executable instructions, the plurality of processor-executable instructions being executed by a processor to perform operations comprising:

• receiving an uncompressed medical video comprising at least one target feature;
• compressing the uncompressed medical video to generate a compressed medical video based on a predicted location of the at least one target feature using a first pretrained machine learning model;
• and,
• detecting a location of the at least one target feature of the compressed medical video using a second pretrained machine learning model,
• wherein the first pretrained machine learning model and the second pretrained machine learning model are trained in tandem using domain-specific medical videos in a manner that, in a first iteration, a training medical video is both compressed and analyzed to detect a location of at least one training target feature before a start of a second iteration after the first iteration, and
• wherein the first pretrained machine learning model is trained to compress a first video frame differently from a second video frame, the first video frame comprising the location of at least one training target feature and the second video frame not comprising the location of at least one training target feature.