Cellpose 2.0: how to train your own model

Abstract excerpt

Generalist models for cellular segmentation, like Cellpose, provide good out-of-the-box results for many types of images. However, such models do not allow users to adapt the segmentation style to their specific needs and may perform sub-optimally for test images that are very different from the training images. Here we introduce Cellpose 2.0, a new package which includes an ensemble of diverse pretrained models a...

Topics

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• Algorithms
• Cell Nucleus
• Deep Learning
• Image Processing, Computer-Assisted
• Machine Learning
• Neural Networks, Computer
• Phenotype
• Radiomics and Machine Learning in Medical Imaging

Identifiers and source

Literature Corpus work

d34d01cf-8a2c-554d-9ac6-14fad73662d7

DOI

10.1101/2022.04.01.486764