Augmentation Technique for Artificial Phase-Contrast Microscopy Image Synthesis for the Training of Deep Learning Algorithms
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F19%3APU137321" target="_blank" >RIV/00216305:26220/19:PU137321 - isvavai.cz</a>
Result on the web
<a href="https://www.researchgate.net/publication/335365184_Augmentation_Technique_for_Artificial_Phase-Contrast_Microscopy_Image_Synthesis_for_the_Training_of_Deep_Learning_Algorithms" target="_blank" >https://www.researchgate.net/publication/335365184_Augmentation_Technique_for_Artificial_Phase-Contrast_Microscopy_Image_Synthesis_for_the_Training_of_Deep_Learning_Algorithms</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Augmentation Technique for Artificial Phase-Contrast Microscopy Image Synthesis for the Training of Deep Learning Algorithms
Original language description
Phase contrast image segmentation is crucial for various biological tasks such as quantitative or comparative analysis at single cell level. Deep learning-based image segmentation has been transferred into the field of microscopy imaging. A large amount of precisely annotated cells is required. Thus, the annotation process is for the experts lengthy and time-consuming. This paper introduces a strategy and augmentation technique for artificial phase-contrast images synthesis aiming to train and support the generalisation ability of deep learning algorithms.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
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OECD FORD branch
20601 - Medical engineering
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů