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Abstract Activated Sludge Membrane Bioreactors (AS-MBR) are recognized as a commercially competitive alternative to conventional wastewater treatments. However, membrane fouling remains one of the main challenges and disadvantages of the process. This study evaluates the suitability of Optical Coherence Tomography (OCT) in monitoring the cake layer development in-situ in AS-MBR under continuous operation. Real-time direct imaging of the cake layer was feasible when limiting the continuous movement of the AS flocs in the reactor by turning aeration off for few minutes prior to scanning a given membrane area. The cake layer morphology was evaluated using both 2D and 3D image analysis. The 3D analysis respect to 2D analysis provided a more representative characterization of the fouling formed in the system. The non-invasive nature of OCT imaging enabled monitoring fouling development over time, where an increase in thickness and a decrease in roughness was observed in the first 200 h of operation. The 3D OCT image analyses were also compared with the 3D confocal laser scanning microscopy (CLSM) image analyses performed at the end of the study. Results demonstrate that OCT imaging can be applied for online, real-time monitoring and analysis of fouling behavior in AS-MBR systems. Graphical abstract Image 1 Highlights • OCT enabled monitoring the fouling in-situ non destructively in real-time in MBR. • The imaging was performed when the reactor aeration was turned off for few minutes. • Fouling deposited on the membrane in the first 120 h was heterogenous. • Over the time the cake layer become thicker and more homogeneous. • 3D analysis respect to 2D analysis was more accurate and more representative. [ABSTRACT FROM AUTHOR]

Optical coherence tomography (OCT) is a non-invasive technique with a large array of applications in clinical imaging and biological tissue visualization. However, the presence of speckle noise affects the analysis of OCT images and their diagnostic utility. In this article, we introduce a new OCT denoising algorithm. The proposed method is founded on a numerical optimization framework based on maximum-a-posteriori estimate of the noise-free OCT image. It combines a novel speckle noise model, derived from local statistics of empirical spectral domain OCT (SD-OCT) data, with a Huber variant of total variation regularization for edge preservation. The proposed approach exhibits satisfying results in terms of speckle noise reduction as well as edge preservation, at reduced computational cost., Competing Interests: The authors declare that there are no conflicts of interest related to this article.