Shapr 3d student4/21/2023 We here show that deep learning can be used to predict the 3D shape of single cells and single nuclei from 2D images and thereby reconstruct relevant morphological information. An application to biomedical imaging, where the tradeoff between resolution and throughput is key, is missing so far. Recently neural networks have been proposed to solve the same task and trained to reconstruct the 3D shape of natural objects from 2D photographs. Reconstructing the shapes of three dimensional (3D) objects from two dimensional (2D) images is a task our brain constantly and unnoticeably performs.
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