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Deep learning-based method for segmenting epithelial layer of tubules in histopathological images of testicular tissue.

Azadeh FakhrzadehPouya KarimianMahsa MeyariCris L Luengo HendriksLena HolmChristian SonneRune DietzEllinor Spörndly-Nees
Published in: Journal of medical imaging (Bellingham, Wash.) (2023)
The pretrained ResNet-34 in the encoder and attention block suggested in the decoder result in better segmentation and generalization. The proposed method can be applied to testicular tissue images from any mammalian species and can be used as the first part of a fully automated testicular tissue processing pipeline. The dataset and codes are publicly available on GitHub.
Keyphrases
  • deep learning
  • convolutional neural network
  • artificial intelligence
  • germ cell
  • machine learning
  • optical coherence tomography
  • high throughput
  • working memory
  • data analysis