Human Epithelial Type 2 cell classification with convolutional neural networks

@article{Bayramoglu2015HumanET,
  title={Human Epithelial Type 2 cell classification with convolutional neural networks},
  author={Neslihan Bayramoglu and Juho Kannala and Janne Heikkil{\"a}},
  journal={2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE)},
  year={2015},
  pages={1-6}
}
Automated cell classification in Indirect Immunofluorescence (IIF) images has potential to be an important tool in clinical practice and research. This paper presents a framework for classification of Human Epithelial Type 2 cell IIF images using convolutional neural networks (CNNs). Previuos state-of-the-art methods show classification accuracy of 75.6% on a benchmark dataset. We conduct an exploration of different strategies for enhancing, augmenting and processing training data in a CNN… CONTINUE READING

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