Systems and methods for surgical video de-identification
AssigneeSst Canada Inc.
InventorsTianbao LI, Shuja KHALID, Kevin YANG, Frank RUDZICZ, Teodor Pantchev GRANTCHAROV
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Abstract
An improved approach is described herein wherein an automated de-identification system is provided to process the raw captured data. The automated de-identification system utilizes specific machine learning data architectures and transforms the raw captured data into processed captured data by modifying, replacing, or obscuring various identifiable features. The processed captured data can include transformed video or audio data.
Claims22
A system for de-identifying raw data including audio or video from one or more input video streams having one or more visual or audible identifiable artifacts, the system comprising:
- a computer processor coupled to a computer memory and one or more non-transitory computer readable media, the computer processor configured to:
- maintain a machine learning model architecture configured to track one or more audio or visual artifacts present in the one or more input video streams and to identify the one or more audio or visual identifiable artifacts as objects for de-identification;
- transform portions of frames of the one or more input video streams to replace the one or more audio or visual identifiable artifacts with corresponding obfuscated replacement audio or visual artifacts;
- and
- generate one or more output video streams including the transformed portions of the frames of the one or more input video streams having the obfuscated replacement audio or visual artifacts.
A method for de-identifying raw data including audio or video from one or more input video streams having one or more visual or audible identifiable artifacts, the method comprising:
- a computer processor coupled to a computer memory and one or more non-transitory computer readable media, the computer processor configured to:
- maintain a machine learning model architecture configured to track one or more audio or visual artifacts present in the one or more input video streams and to identify the one or more audio or visual identifiable artifacts as objects for de-identification;
- transform portions of frames of the one or more input video streams to replace the one or more audio or visual identifiable artifacts with corresponding obfuscated replacement audio or visual artifacts;
- and
- generate one or more output video streams including the transformed portions of the frames of the one or more input video streams having the obfuscated replacement audio or visual artifacts.
(canceled)
A non-transitory computer readable medium storing machine interpretable instructions, which when executed by a processor, cause the processor to perform a method for for de-identifying raw data including audio or video from one or more input video streams having one or more visual or audible identifiable artifacts, the method comprising:
- a computer processor coupled to a computer memory and one or more non-transitory computer readable media, the computer processor configured to:
- maintain a machine learning model architecture configured to track one or more audio or visual artifacts present in the one or more input video streams and to identify the one or more audio or visual identifiable artifacts as objects for de-identification;
- transform portions of frames of the one or more input video streams to replace the one or more audio or visual identifiable artifacts with corresponding obfuscated replacement audio or visual artifacts;
- and
- generate one or more output video streams including the transformed portions of the frames of the one or more input video streams having the obfuscated replacement audio or visual artifacts.
22-30. (canceled)
Dependencies are inferred from the claim text.