Breast cancer histopathology image analysis: A review

M Veta, JPW Pluim, PJ Van Diest… - IEEE transactions on …, 2014 - ieeexplore.ieee.org
This paper presents an overview of methods that have been proposed for the analysis of
breast cancer histopathology images. This research area has become particularly relevant …

Digital image analysis in breast pathology—from image processing techniques to artificial intelligence

S Robertson, H Azizpour, K Smith, J Hartman - Translational Research, 2018 - Elsevier
Breast cancer is the most common malignant disease in women worldwide. In recent
decades, earlier diagnosis and better adjuvant therapy have substantially improved patient …

Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent

A Cruz-Roa, H Gilmore, A Basavanhally, M Feldman… - Scientific reports, 2017 - nature.com
With the increasing ability to routinely and rapidly digitize whole slide images with slide
scanners, there has been interest in developing computerized image analysis algorithms for …

Performance analysis of seven Convolutional Neural Networks (CNNs) with transfer learning for Invasive Ductal Carcinoma (IDC) grading in breast histopathological …

W Voon, YC Hum, YK Tee, WS Yap, MIM Salim… - Scientific reports, 2022 - nature.com
Abstract Computer-aided Invasive Ductal Carcinoma (IDC) grading classification systems
based on deep learning have shown that deep learning may achieve reliable accuracy in …

Pre‐trained convolutional neural networks as feature extractors for diagnosis of breast cancer using histopathology

S Saxena, S Shukla… - International Journal of …, 2020 - Wiley Online Library
Several researchers are trying to develop different computer‐aided diagnosis system for
breast cancer employing machine learning (ML) methods. The inputs to these ML algorithms …

Automated grading of breast cancer histopathology using cascaded ensemble with combination of multi-level image features

T Wan, J Cao, J Chen, Z Qin - Neurocomputing, 2017 - Elsevier
We present a novel image-analysis based method for automatically distinguishing low,
intermediate, and high grades of breast cancer in digitized histopathology. A multiple level …

Nuclear atypia grading in breast cancer histopathological images based on CNN feature extraction and LSTM classification

S Karimi Jafarbigloo, H Danyali - CAAI Transactions on …, 2021 - Wiley Online Library
Early diagnosis of breast cancer, the most common disease among women around the
world, increases the chance of treatment and is highly important. Nuclear atypia grading in …

Evaluating cancer-related biomarkers based on pathological images: a systematic review

X Xie, X Wang, Y Liang, J Yang, Y Wu, L Li… - Frontiers in …, 2021 - frontiersin.org
Many diseases are accompanied by changes in certain biochemical indicators called
biomarkers in cells or tissues. A variety of biomarkers, including proteins, nucleic acids …

[PDF][PDF] Histopathological image analysis using image processing techniques: An overview

AD Belsare, MM Mushrif - Signal & Image Processing, 2012 - researchgate.net
This paper reviews computer assisted histopathology image analysis for cancer detection
and classification. Histopathology refers to the examination of invasive or less invasive …

Evaluating the effectiveness of stain normalization techniques in automated grading of invasive ductal carcinoma histopathological images

W Voon, YC Hum, YK Tee, WS Yap, H Nisar… - Scientific Reports, 2023 - nature.com
Debates persist regarding the impact of Stain Normalization (SN) on recent breast cancer
histopathological studies. While some studies propose no influence on classification …