Breast cancer histopathology image analysis: A review
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 …
breast cancer histopathology images. This research area has become particularly relevant …
Digital image analysis in breast pathology—from image processing techniques to artificial intelligence
Breast cancer is the most common malignant disease in women worldwide. In recent
decades, earlier diagnosis and better adjuvant therapy have substantially improved patient …
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
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 …
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 …
Abstract Computer-aided Invasive Ductal Carcinoma (IDC) grading classification systems
based on deep learning have shown that deep learning may achieve reliable accuracy in …
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
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 …
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
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 …
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 …
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 …
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 …
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
Debates persist regarding the impact of Stain Normalization (SN) on recent breast cancer
histopathological studies. While some studies propose no influence on classification …
histopathological studies. While some studies propose no influence on classification …