Fig. 1: Interpolation workflow and test datasets. | Nature Methods

Fig. 1: Interpolation workflow and test datasets.

From: InterpolAI: deep learning-based optical flow interpolation and restoration of biomedical images for improved 3D tissue mapping

Fig. 1

a, Samples were obtained from two species, mouse and human. Four different organs were analyzed: human pancreas, human brain, mouse brain and mouse lung. Five imaging modalities were tested: H&E-stained histological slides, IHC stained histological slides, MRI, serial ssTEM slides and combined tissue clearing and light-sheet microscopy. b, Aligned slides are manually searched through to identify missing or damaged slides, and damaged slides are removed from the stack of slides. InterpolAI interpolation is performed using the sections adjacent to the damaged or missing slides as inputs to recreate slides that were stained differently, missing or damaged, resulting in a uniform stack of slides. Using CODA, slides are segmented into labeled tissue masks, with each label representing a different microanatomical structure in the slide, which is then used to recreate and visualize microanatomical 3D structures in the tissue sample. Illustrations created using BioRender.com.

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