Deep Learning With Conformal Prediction for Hierarchical Analysis of Large-Scale Whole-Slide Tissue Images

@article{Wieslander2021DeepLW,
  title={Deep Learning With Conformal Prediction for Hierarchical Analysis of Large-Scale Whole-Slide Tissue Images},
  author={H{\aa}kan Wieslander and Philip John Harrison and Gabriel Skogberg and Sonya Jackson and Marcus Friden and Johan Karlsson and Ola Spjuth and Carolina W{\"a}hlby},
  journal={IEEE Journal of Biomedical and Health Informatics},
  year={2021},
  volume={25},
  pages={371-380}
}
With the increasing amount of image data collected from biomedical experiments there is an urgent need for smarter and more effective analysis methods. Many scientific questions require analysis of image sub-regions related to some specific biology. Finding such regions of interest (ROIs) at low resolution and limiting the data subjected to final quantification at full resolution can reduce computational requirements and save time. In this paper we propose a three-step pipeline: First, bounding… 

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