A comprehensive review of computer-aided whole-slide image analysis: from datasets to feature extraction, segmentation, classification and detection approaches
With the development of Computer-aided Diagnosis (CAD) and image scanning techniques,
Whole-slide Image (WSI) scanners are widely used in the field of pathological diagnosis …
Whole-slide Image (WSI) scanners are widely used in the field of pathological diagnosis …
A survey on graph-based deep learning for computational histopathology
With the remarkable success of representation learning for prediction problems, we have
witnessed a rapid expansion of the use of machine learning and deep learning for the …
witnessed a rapid expansion of the use of machine learning and deep learning for the …
Dual-stream multiple instance learning network for whole slide image classification with self-supervised contrastive learning
We address the challenging problem of whole slide image (WSI) classification. WSIs have
very high resolutions and usually lack localized annotations. WSI classification can be cast …
very high resolutions and usually lack localized annotations. WSI classification can be cast …
Weakly supervised deep learning for whole slide lung cancer image analysis
Histopathology image analysis serves as the gold standard for cancer diagnosis. Efficient
and precise diagnosis is quite critical for the subsequent therapeutic treatment of patients …
and precise diagnosis is quite critical for the subsequent therapeutic treatment of patients …
Multi-scale domain-adversarial multiple-instance CNN for cancer subtype classification with unannotated histopathological images
N Hashimoto, D Fukushima, R Koga… - Proceedings of the …, 2020 - openaccess.thecvf.com
We propose a new method for cancer subtype classification from histopathological images,
which can automatically detect tumor-specific features in a given whole slide image (WSI) …
which can automatically detect tumor-specific features in a given whole slide image (WSI) …
Breast cancer detection, segmentation and classification on histopathology images analysis: a systematic review
R Krithiga, P Geetha - Archives of Computational Methods in Engineering, 2021 - Springer
Digital pathology represents a major evolution in modern medicine. Pathological
examinations constitute the standard in medical protocols and the law, and call for specific …
examinations constitute the standard in medical protocols and the law, and call for specific …
Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies
B Ehteshami Bejnordi, M Mullooly, RM Pfeiffer… - Modern …, 2018 - nature.com
The breast stromal microenvironment is a pivotal factor in breast cancer development,
growth and metastases. Although pathologists often detect morphologic changes in stroma …
growth and metastases. Although pathologists often detect morphologic changes in stroma …
Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images
Currently, histopathological tissue examination by a pathologist represents the gold
standard for breast lesion diagnostics. Automated classification of histopathological whole …
standard for breast lesion diagnostics. Automated classification of histopathological whole …
Boosting whole slide image classification from the perspectives of distribution, correlation and magnification
Bag-based multiple instance learning (MIL) methods have become the mainstream for
Whole Slide Image (WSI) classification. However, there are still three important issues that …
Whole Slide Image (WSI) classification. However, there are still three important issues that …
Differentiable zooming for multiple instance learning on whole-slide images
Abstract Multiple Instance Learning (MIL) methods have become increasingly popular for
classifying gigapixel-sized Whole-Slide Images (WSIs) in digital pathology. Most MIL …
classifying gigapixel-sized Whole-Slide Images (WSIs) in digital pathology. Most MIL …