Deep learning in histopathology: the path to the clinic

J Van der Laak, G Litjens, F Ciompi - Nature medicine, 2021 - nature.com
Abstract Machine learning techniques have great potential to improve medical diagnostics,
offering ways to improve accuracy, reproducibility and speed, and to ease workloads for …

Deep neural network models for computational histopathology: A survey

CL Srinidhi, O Ciga, AL Martel - Medical image analysis, 2021 - Elsevier
Histopathological images contain rich phenotypic information that can be used to monitor
underlying mechanisms contributing to disease progression and patient survival outcomes …

[HTML][HTML] The impact of pre-and post-image processing techniques on deep learning frameworks: A comprehensive review for digital pathology image analysis

M Salvi, UR Acharya, F Molinari… - Computers in Biology and …, 2021 - Elsevier
Recently, deep learning frameworks have rapidly become the main methodology for
analyzing medical images. Due to their powerful learning ability and advantages in dealing …

A novel deep learning based framework for the detection and classification of breast cancer using transfer learning

SU Khan, N Islam, Z Jan, IU Din… - Pattern Recognition …, 2019 - Elsevier
Breast cancer is among the leading cause of mortality among women in developing as well
as under-developing countries. The detection and classification of breast cancer in the early …

Bach: Grand challenge on breast cancer histology images

G Aresta, T Araújo, S Kwok, SS Chennamsetty… - Medical image …, 2019 - Elsevier
Breast cancer is the most common invasive cancer in women, affecting more than 10% of
women worldwide. Microscopic analysis of a biopsy remains one of the most important …

Breast cancer histopathological image classification using a hybrid deep neural network

R Yan, F Ren, Z Wang, L Wang, T Zhang, Y Liu, X Rao… - Methods, 2020 - Elsevier
Even with the rapid advances in medical sciences, histopathological diagnosis is still
considered the gold standard in diagnosing cancer. However, the complexity of …

Going deep in medical image analysis: concepts, methods, challenges, and future directions

F Altaf, SMS Islam, N Akhtar, NK Janjua - IEEE Access, 2019 - ieeexplore.ieee.org
Medical image analysis is currently experiencing a paradigm shift due to deep learning. This
technology has recently attracted so much interest of the Medical Imaging Community that it …

A comprehensive review for breast histopathology image analysis using classical and deep neural networks

X Zhou, C Li, MM Rahaman, Y Yao, S Ai, C Sun… - IEEE …, 2020 - ieeexplore.ieee.org
Breast cancer is one of the most common and deadliest cancers among women. Since
histopathological images contain sufficient phenotypic information, they play an …

Optimizing the performance of breast cancer classification by employing the same domain transfer learning from hybrid deep convolutional neural network model

L Alzubaidi, O Al-Shamma, MA Fadhel, L Farhan… - Electronics, 2020 - mdpi.com
Breast cancer is a significant factor in female mortality. An early cancer diagnosis leads to a
reduction in the breast cancer death rate. With the help of a computer-aided diagnosis …

A survey on artificial intelligence in histopathology image analysis

MM Abdelsamea, U Zidan, Z Senousy… - … : Data Mining and …, 2022 - Wiley Online Library
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 …