A survey on artificial intelligence in histopathology image analysis
The increasing adoption of the whole slide image (WSI) technology in histopathology has
dramatically transformed pathologists' workflow and allowed the use of computer systems in …
dramatically transformed pathologists' workflow and allowed the use of computer systems in …
Towards label-efficient automatic diagnosis and analysis: a comprehensive survey of advanced deep learning-based weakly-supervised, semi-supervised and self …
Histopathological images contain abundant phenotypic information and pathological
patterns, which are the gold standards for disease diagnosis and essential for the prediction …
patterns, which are the gold standards for disease diagnosis and essential for the prediction …
Cancer survival prediction from whole slide images with self-supervised learning and slide consistency
L Fan, A Sowmya, E Meijering… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Histopathological Whole Slide Images (WSIs) at giga-pixel resolution are the gold standard
for cancer analysis and prognosis. Due to the scarcity of pixel-or patch-level annotations of …
for cancer analysis and prognosis. Due to the scarcity of pixel-or patch-level annotations of …
Colour adaptive generative networks for stain normalisation of histopathology images
Deep learning has shown its effectiveness in histopathology image analysis, such as
pathology detection and classification. However, stain colour variation in Hematoxylin and …
pathology detection and classification. However, stain colour variation in Hematoxylin and …
A stain color normalization with robust dictionary learning for breast cancer histological images processing
Microscopic analyses of tissue samples are crucial for confirming the diagnosis of breast
cancer. The digitization of these samples has led to the development of computational …
cancer. The digitization of these samples has led to the development of computational …
Domain generalization in computational pathology: survey and guidelines
Deep learning models have exhibited exceptional effectiveness in Computational Pathology
(CPath) by tackling intricate tasks across an array of histology image analysis applications …
(CPath) by tackling intricate tasks across an array of histology image analysis applications …
Fast FF-to-FFPE whole slide image translation via Laplacian pyramid and contrastive learning
Abstract Formalin-Fixed Paraffin-Embedded (FFPE) and Fresh Frozen (FF) are two major
types of histopathological Whole Slide Images (WSIs). FFPE provides high-quality images …
types of histopathological Whole Slide Images (WSIs). FFPE provides high-quality images …
A laplacian pyramid based generative h&e stain augmentation network
Hematoxylin and Eosin (H&E) staining is a widely used sample preparation procedure for
enhancing the saturation of tissue sections and the contrast between nuclei and cytoplasm …
enhancing the saturation of tissue sections and the contrast between nuclei and cytoplasm …
HistoStarGAN: A unified approach to stain normalisation, stain transfer and stain invariant segmentation in renal histopathology
Virtual stain transfer is a promising area of research in Computational Pathology, which has
a great potential to alleviate important limitations when applying deep-learning-based …
a great potential to alleviate important limitations when applying deep-learning-based …
Stain-aglr: Stain agnostic learning for computational histopathology using domain consistency and stain regeneration loss
G Raipuria, A Shrivastava, N Singhal - MICCAI Workshop on Domain …, 2022 - Springer
Stain color variations between Whole Slide Images (WSIs) is a key challenge in the
application of Computational Histopathology. Deep learning-based algorithms are …
application of Computational Histopathology. Deep learning-based algorithms are …