US 12,402,853 B2
Systems and methods for real-time video enhancement
David Van Veen, San Francisco, CA (US); Long Wang, Sunnyvale, CA (US); Ben Andrew Duffy, Mountain View, CA (US); Enhao Gong, Sunnyvale, CA (US); and Tao Zhang, Menlo Park, CA (US)
Assigned to SUBTLE MEDICAL, INC., Menlo Park, CA (US)
Filed by Subtle Medical, Inc., Menlo Park, CA (US)
Filed on Aug. 4, 2022, as Appl. No. 17/880,831.
Application 17/880,831 is a continuation of application No. PCT/US2021/017189, filed on Feb. 9, 2021.
Claims priority of provisional application 62/972,999, filed on Feb. 11, 2020.
Prior Publication US 2023/0038871 A1, Feb. 9, 2023
Int. Cl. G06T 5/00 (2024.01); A61B 6/00 (2006.01); G06T 5/50 (2006.01); G06T 5/70 (2024.01); G06V 10/82 (2022.01)
CPC A61B 6/542 (2013.01) [A61B 6/5258 (2013.01); G06T 5/50 (2013.01); G06T 5/70 (2024.01); G06V 10/82 (2022.01); G06T 2207/10016 (2013.01); G06T 2207/10121 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20216 (2013.01); G06T 2207/30004 (2013.01); G06T 2207/30168 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A computer-implemented method for improving live video quality comprising:
(a) acquiring, using a medical imaging apparatus, a stream of consecutive image frames of a subject, wherein the stream of consecutive image frames is acquired with a reduced amount of radiation dose;
(b) applying a deep learning network model to the stream of consecutive image frames to generate an output image frame with improved quality in both temporal domain and spatial domain, wherein the deep learning network model is trained using training datasets comprising a pair of a simulated low-quality video and a simulated high-quality video; and
(c) displaying the output image frame with improved quality in real-time on a display.