A comprehensive review of computer-aided whole-slide image analysis: from datasets to feature extraction, segmentation, classification and detection approaches

X Li, C Li, MM Rahaman, H Sun, X Li, J Wu… - Artificial Intelligence …, 2022 - Springer
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 …

Pathology imaging informatics for quantitative analysis of whole-slide images

S Kothari, JH Phan, TH Stokes… - Journal of the American …, 2013 - academic.oup.com
Objectives With the objective of bringing clinical decision support systems to reality, this
article reviews histopathological whole-slide imaging informatics methods, associated …

A generalized deep learning framework for whole-slide image segmentation and analysis

M Khened, A Kori, H Rajkumar, G Krishnamurthi… - Scientific reports, 2021 - nature.com
Histopathology tissue analysis is considered the gold standard in cancer diagnosis and
prognosis. Whole-slide imaging (WSI), ie, the scanning and digitization of entire histology …

[HTML][HTML] Introduction to digital image analysis in whole-slide imaging: a white paper from the digital pathology association

F Aeffner, MD Zarella, N Buchbinder, MM Bui… - Journal of pathology …, 2019 - Elsevier
The advent of whole-slide imaging in digital pathology has brought about the advancement
of computer-aided examination of tissue via digital image analysis. Digitized slides can now …

[HTML][HTML] Classification of melanocytic lesions in selected and whole-slide images via convolutional neural networks

SN Hart, W Flotte, F Andrew, KK Shah… - Journal of Pathology …, 2019 - Elsevier
Whole-slide images (WSIs) are a rich new source of biomedical imaging data. The use of
automated systems to classify and segment WSIs has recently come to forefront of the …

Deep-Hipo: Multi-scale receptive field deep learning for histopathological image analysis

SC Kosaraju, J Hao, HM Koh, M Kang - Methods, 2020 - Elsevier
Digitizing whole-slide imaging in digital pathology has led to the advancement of computer-
aided tissue examination using machine learning techniques, especially convolutional …

Whole-slide imaging: routine pathologic diagnosis

TC Cornish, RE Swapp, KJ Kaplan - Advances in anatomic …, 2012 - journals.lww.com
Digital pathology systems offer pathologists an alternate, emerging mechanism to manage
and interpret information. They offer increasingly fast and scalable hardware platforms for …

[HTML][HTML] Resolution-agnostic tissue segmentation in whole-slide histopathology images with convolutional neural networks

P Bándi, M Balkenhol, B van Ginneken, J van der Laak… - PeerJ, 2019 - peerj.com
Modern pathology diagnostics is being driven toward large scale digitization of microscopic
tissue sections. A prerequisite for its safe implementation is the guarantee that all tissue …

[HTML][HTML] Twenty years of digital pathology: an overview of the road travelled, what is on the horizon, and the emergence of vendor-neutral archives

L Pantanowitz, A Sharma, AB Carter, T Kurc… - Journal of pathology …, 2018 - Elsevier
Almost 20 years have passed since the commercial introduction of whole-slide imaging
(WSI) scanners. During this time, the creation of various WSI devices with the ability to …

High-throughput adaptive sampling for whole-slide histopathology image analysis (HASHI) via convolutional neural networks: Application to invasive breast cancer …

A Cruz-Roa, H Gilmore, A Basavanhally, M Feldman… - PloS one, 2018 - journals.plos.org
Precise detection of invasive cancer on whole-slide images (WSI) is a critical first step in
digital pathology tasks of diagnosis and grading. Convolutional neural network (CNN) is the …