Detail publikace

Augmentation Technique for Artificial Phase-Contrast Microscopy Image Synthesis for the Training of Deep Learning Algorithms

MÍVALT, F.

Originální název

Augmentation Technique for Artificial Phase-Contrast Microscopy Image Synthesis for the Training of Deep Learning Algorithms

Typ

článek ve sborníku mimo WoS a Scopus

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

deep learning, phase-contrast, cell segmentation, data augmentation, artificial data gen- eration

Autoři

MÍVALT, F.

Vydáno

25. 4. 2019

Místo

Brno

ISBN

978-80-214-5735

Kniha

Proceedings of the 25th Conference STUDENT EEICT 2019

Číslo edice

1

Strany od

199

Strany do

202

Strany počet

2

URL

https://www.researchgate.net/publication/335365184_Augmentation_Technique_for_Artificial_Phase-Contrast_Microscopy_Image_Synthesis_for_the_Training_of_Deep_Learning_Algorithms

BibTex

@inproceedings{BUT165371,
  author="Filip {Mívalt}",
  title="Augmentation Technique for Artificial Phase-Contrast Microscopy Image Synthesis for the Training of Deep Learning Algorithms",
  booktitle="Proceedings of the 25th Conference STUDENT EEICT 2019",
  year="2019",
  number="1",
  pages="199--202",
  address="Brno",
  doi="10.13140/RG.2.2.32827.16160",
  isbn="978-80-214-5735",
  url="https://www.researchgate.net/publication/335365184_Augmentation_Technique_for_Artificial_Phase-Contrast_Microscopy_Image_Synthesis_for_the_Training_of_Deep_Learning_Algorithms"
}