CAD systems for colorectal cancer from WSI are still not ready for clinical acceptance
Most oncological cases can be detected by imaging techniques, but diagnosis is based on
pathological assessment of tissue samples. In recent years, the pathology field has evolved …
pathological assessment of tissue samples. In recent years, the pathology field has evolved …
A comprehensive survey of intestine histopathological image analysis using machine vision approaches
Y Jing, C Li, T Du, T Jiang, H Sun, J Yang, L Shi… - Computers in Biology …, 2023 - Elsevier
Colorectal Cancer (CRC) is currently one of the most common and deadly cancers. CRC is
the third most common malignancy and the fourth leading cause of cancer death worldwide …
the third most common malignancy and the fourth leading cause of cancer death worldwide …
IL-MCAM: An interactive learning and multi-channel attention mechanism-based weakly supervised colorectal histopathology image classification approach
In recent years, colorectal cancer has become one of the most significant diseases that
endanger human health. Deep learning methods are increasingly important for the …
endanger human health. Deep learning methods are increasingly important for the …
Crccn-net: Automated framework for classification of colorectal tissue using histopathological images
Colorectal cancer has a high mortality rate that continuously affects human life globally.
Early detection of it extends human life and helps in preventing disease. Histopathological …
Early detection of it extends human life and helps in preventing disease. Histopathological …
An efficient deep learning approach for colon cancer detection
Colon cancer is the second most common cause of cancer death in women and the third
most common cause of cancer death in men. Therefore, early detection of this cancer can …
most common cause of cancer death in men. Therefore, early detection of this cancer can …
A convolution neural network with multi-level convolutional and attention learning for classification of cancer grades and tissue structures in colon histopathological …
A clinically comparable Convolutional Neural Network framework-based technique for
performing automated classification of cancer grades and tissue structures in hematoxylin …
performing automated classification of cancer grades and tissue structures in hematoxylin …
Automated detection and classification of leukemia on a subject-independent test dataset using deep transfer learning supported by Grad-CAM visualization
Leukemia is a type of cancer that affects blood cells and causes fatal infection and
premature death. Modern technology enabled by the machine and advanced deep learning …
premature death. Modern technology enabled by the machine and advanced deep learning …
Improving machine learning recognition of colorectal cancer using 3D GLCM applied to different color spaces
AM Alqudah, A Alqudah - Multimedia Tools and Applications, 2022 - Springer
Colorectal cancer (CRC) is one of the widely happening cancers among men and women.
This cancer, which is also known as bowel cancer, affects the human large intestine …
This cancer, which is also known as bowel cancer, affects the human large intestine …
Ensemble of adapted convolutional neural networks (CNN) methods for classifying colon histopathological images
D Albashish - PeerJ Computer Science, 2022 - peerj.com
Deep convolutional neural networks (CNN) manifest the potential for computer-aided
diagnosis systems (CADs) by learning features directly from images rather than using …
diagnosis systems (CADs) by learning features directly from images rather than using …
Multiclass colorectal cancer histology images classification using vision transformers
MAE Zeid, K El-Bahnasy… - 2021 tenth international …, 2021 - ieeexplore.ieee.org
Colorectal cancer (CRC) is the third most diagnosed cancer form globally and the second
leading cause of cancer-related death after lung cancer. A precise histological …
leading cause of cancer-related death after lung cancer. A precise histological …