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Data · dataset · 2022

UT-GPCR002 Machine learning models for CHO-K1 cell segmentation from fluorescence and bright-field microscopy images

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The "UT-GPCR002 Machine learning models for CHO-K1 cell segmentation from fluorescence and bright-field microscopy images" dataset contains the machine learning model files for CHO-K1 cell segmentation from fluorescence and bright-field microscopy images.

Description

Random forest-based models are implemented as Ilastik projects while deep-learning models are implemented in Keras.

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Catalogue records · 1

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Life Sciences
Inferred from text
Biochemistry and cell biology 73% · Image 65% · Microscopy 75%
Provenance · 1 source records, 11 field assertions
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DATADOIdoi:10.23673/RE-30413 d agoJSON v1
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concepts[modality].local:modality:imageenrichment · datadoi eekeyword-concept-rules@1.0.0title+description (65%)
concepts[modality].local:modality:microscopyenrichment · datadoi eekeyword-concept-rules@1.0.0title+description (75%)
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