Towards Label-efficient Automatic Diagnosis and Analysis: A Comprehensive Survey of Advanced Deep Learning-based Weakly-supervised, Semi-supervised and Self-supervised Techniques in Histopathological Image Analysis. (arXiv:2208.08789v1 [cs.CV])

Histopathological images contain abundant phenotypic information and
pathological patterns, which are the gold standards for disease diagnosis and
essential for the prediction of patient prognosis and treatment outcome. In
recent years, computer-automated analysis techniques for histopathological
images have been urgently required in clinical practice, and deep learning
methods represented by convolutional neural networks have gradually become the
mainstream in the field of digital pathology. However, obtaining large numbers
of fine-grained annotated data in this field is a very expensive and …

analysis arxiv cv deep learning diagnosis image learning semi-supervised survey weakly-supervised