Augmentation Technique For Artificial Phase-Contrast Microscopy Images Generation For The Training Of Deep Learning Algorithms
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Phase contrast segmentation is crucial for various biological tasks such us quantitative, comparative or single cell level analysis. The popularity of image segmentation using deep learning strategies has been transferred into the field of microscopy imaging as well. Since the huge amount of training data is usually required, the annotation is time-consuming and lengthy. This paper introduces the method and augmentation techniques for artificial phase-contrast images generation aiming at the training of deep learning algorithms.
Keywordsdeep learning, phase-contrast, cell segmentation, data augmentation, artificial data generation
Document typePeer reviewed
Document versionxmlui.vut.verze.Publishers's version
SourceProceedings of the 25st Conference STUDENT EEICT 2019. s. 199-202. ISBN 978-80-214-5735-5
- Student EEICT 2019