Dataset in support of the paper 'Diatom Lensless imaging using laser scattering and deep learning'

Abstract

Paper published in ACS ES&T Water. https://doi.org/10.1021/acsestwater.4c01186 This dataset contains: Figure_1. a) Diagram of the experimental setup used to simultaneously image the diatoms and capture their scattering pattern from laser illumination. Three neural networks employed in this work were b) image generation, c) speed classification, and d) angular direction classification. Figure_2. Experimental diatom scattering patterns (column 1) and the associated neural network predicted images (column 2). Also included are the corresponding experimental images (column 3) and the difference between the two images (column 4) (one minus the other, such that white pixels indicate less difference). Figure_3. a) Predicted diatom velocity compared with experimental velocity. b) Predicted diatom angle compared with experimental angle when moving at a velocity of 0.2 mm/s. Test data 1 is data from angles used during training of the neural network, whilst test data 2 is data from angles not present in the training data. Table_1 PSNR, SSIM, RMSE and PIQE for the predicted and experimental pollen images shown in Figure 2. TOC_Graphic Table of contents graphic.

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