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Image processing is manipulation of an image that has been digitised and uploaded into a computer. Software programs modify the image to make it more useful, and can for example be used to enable image recognition.
A deep learning model—OrgaSegment—is presented for segmentation of individual intestinal patient-derived organoid structures from bright-field images. This enables quantification of organoid swelling and discrimination between organoids with different levels CFTR function and response to therapy.
Picking particles of biological macromolecules is critical for solving their structures in situ using cryo-electron tomograms. Here, authors develop DeepETPicker, a deep learning-based tool for fast, accurate, and automated picking of three-dimensional particles.
The visualization and analysis of biological events using fluorescence microscopy is limited by the noise inherent in the images obtained. Now, a self-supervised spatial redundancy denoising transformer is proposed to address this challenge.