US 12,444,051 B2
System for OCT image translation, ophthalmic image denoising, and neural network therefor
Arindam Bhattacharya, Dublin, CA (US); Warren Lewis, Yellow Springs, OH (US); Sophie Kubach, Menlo Park, CA (US); Lars Omlor, Pleasanton, CA (US); and Mary Durbin, San Francisco, CA (US)
Assigned to CARL ZEISS MEDITEC, INC., Dublin, CA (US); and CARL ZEISS MEDITEC AG, Jena (DE)
Appl. No. 17/428,122
Filed by Carl Zeiss Meditec AG, Jena (DE); and Carl Zeiss Meditec, Inc., Dublin, CA (US)
PCT Filed Feb. 12, 2020, PCT No. PCT/EP2020/053515
§ 371(c)(1), (2) Date Aug. 3, 2021,
PCT Pub. No. WO2020/165196, PCT Pub. Date Aug. 20, 2020.
Claims priority of provisional application 62/805,835, filed on Feb. 14, 2019.
Prior Publication US 2022/0058803 A1, Feb. 24, 2022
Int. Cl. G06T 7/00 (2017.01); A61B 3/10 (2006.01); G06T 5/50 (2006.01); G06T 5/70 (2024.01); G06T 7/37 (2017.01); G06T 11/00 (2006.01); G16H 30/40 (2018.01)
CPC G06T 7/0014 (2013.01) [A61B 3/102 (2013.01); G06T 5/50 (2013.01); G06T 5/70 (2024.01); G06T 7/37 (2017.01); G06T 11/008 (2013.01); G16H 30/40 (2018.01); G06T 2207/10084 (2013.01); G06T 2207/10101 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30041 (2013.01)] 27 Claims
OG exemplary drawing
 
1. An optical coherence tomography (OCT) system comprising:
a light source for generating a beam of light;
a beam splitter having a beam-splitting surface for directing a first portion of the light into a reference arm and a second portion of the light into a sample arm;
optics for directing the light in the sample arm to one or more locations on a sample;
a detector for receiving light returning from the sample and reference arms and generating signals in response thereto;
a processor for converting the signals into a first image and submitting the first image to an image translation module that translates the first image to a second image characterized by one or more of decreased noise artifacts, jitter and minimized creation of fictional structures as compared to the first image; and
an output display for displaying a system output image based on the second image;
wherein the image translation module includes a machine learning module based on a neural network trained using a set of training input images and a target set of training output images,
wherein the neural network has an input module configured to receive a current training input image, a plurality of intermediate processing modules following the input module, an intermediate error module that determines an intermediate error based on an output of at least one select intermediate processing module and a current training output image, and an output module following the plurality of intermediate processing modules that determines a preliminary output error based on its output and the current training output image, and
wherein a total loss error for a current training cycle is defined based on a combination of the preliminary output error and the intermediate error.