Optical coherence tomography (OCT) is an optical imaging method based on low-coherence interferometry. OCT uses light waves to take cross-section images of your internal
microstructure such as retina by measuring light backscattered from the sample. It can
provide reliable and high resolution images of biological tissues at different levels.
Real-time OCT can be a challenge due to the heavy computational load required
to process acquired data streams. Reconstructing functional images with multi-functional
OCT imaging requires additional processing, further increasing processing time.
So we introduced graphics processing unit (GPU) processing and some code opti-
mization strategies of MATLAB to accelerate the image processing. Also, we implemented
a web application to run MATLAB program remotely for the convenience of the researchers.
It can allow multiple users to remote control MATLAB programs and do some basic oper-
ations through both mobile phone and computer.
In Chapter1, I will explain the OCT data processing workflow and describe the
motivation of OCT data processing acceleration.
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Chapter2 will mainly focus on the methods that I used to improve the performance
of the MATLAB code and show the comparison of the total processing time.
In Chapter3, I will introduce the features of the web application as well as the
structure of the whole application for both front-end and back-end.
Chapter4 is the conclusion part of the entire post-processing acceleration project,
some future work will also be listed in chapter4.