Correr-Zhou/RepMode
[CVPR 2023 (Highlight)] Offical implementation of the paper "RepMode: Learning to Re-parameterize Diverse Experts for Subcellular Structure Prediction".
This tool helps cell biologists and researchers working with microscopy data to predict the 3D locations of multiple subcellular structures within a cell. You input a 3D transmitted-light microscope image of a cell, and it outputs detailed 3D fluorescent images showing where specific organelles and structures are located. This is for scientists analyzing cell morphology and function.
165 stars. No commits in the last 6 months.
Use this if you need to accurately identify and visualize the 3D distribution of multiple subcellular structures from standard transmitted-light microscopy without requiring costly and time-consuming fluorescent labeling for every structure.
Not ideal if you are working with 2D images or do not have access to high-performance computing resources like a powerful GPU and substantial RAM.
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Python
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Last pushed
Oct 12, 2023
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