HistoKT: Cross Knowledge Transfer in Computational Pathology. (arXiv:2201.11246v1 [eess.IV])

Web: http://arxiv.org/abs/2201.11246

The lack of well-annotated datasets in computational pathology (CPath)
obstructs the application of deep learning techniques for classifying medical
images. %Since pathologist time is expensive, dataset curation is intrinsically
difficult. Many CPath workflows involve transferring learned knowledge between
various image domains through transfer learning. Currently, most transfer
learning research follows a model-centric approach, tuning network parameters
to improve transfer results over few datasets. In this paper, we take a
data-centric approach to the transfer learning problem and examine the
existence …

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