Automated image processing algorithm for 3D OCT images of fouling in spacer-filled membrane filtration channels

Abstract

OCT imaging is an important technique to study fouling in spacer-filled channels of reverse osmosis systems for seawater desalination. However, OCT imaging of membrane filtration channels with feed spacers is challenging because the spacer material can be (partly) transparent, making it difficult to detect and possibly mistaken for fouling, and the longer optical pathway through the spacer material distorts the image below the spacer. This study presents an automated 3D OCT image processing method in MATLAB for visualization and quantification of biofouling in spacer-filled channels. First, a spacer template of arbitrary size and rotation was generated from a CT scan of the feed spacer. Second, background noise and file size were reduced by representing the OCT image with a list of discrete reflectors. Finally, the spacer template was overlayed with the feed spacer in the 3D OCT image, enabling automated visualization of the feed spacer and correction of the distortions. Moreover, the method allows the selection of datasets with the same location relative to the position of the spacer, enabling systematic comparison between datasets and quantitative analysis.

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  A spacer template of arbitrary size and rotation was generated from a CT scan.

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  The background noise was removed, and the file size was reduced by representing the OCT dataset with a list of discrete reflectors.

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  The spacer template was overlayed with the feed spacer in the 3D OCT image.