A novel transfer learning approach for the classification of histological images of colorectal cancer
EF Ohata, JVS Chagas, GM Bezerra… - The Journal of …, 2021 - Springer
Colorectal cancer (CRC) is the second most diagnosed cancer in the United States. It is
identified by histopathological evaluations of microscopic images of the cancerous region …
identified by histopathological evaluations of microscopic images of the cancerous region …
[PDF][PDF] Colorectal cancer classification using deep convolutional networks
The analysis of histological samples is of paramount importance for the early diagnosis of
colorectal cancer (CRC). The traditional visual assessment is time-consuming and highly …
colorectal cancer (CRC). The traditional visual assessment is time-consuming and highly …
[HTML][HTML] 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 …
[HTML][HTML] Deep learning techniques for the classification of colorectal cancer tissue
MJ Tsai, YH Tao - Electronics, 2021 - mdpi.com
It is very important to make an objective evaluation of colorectal cancer histological images.
Current approaches are generally based on the use of different combinations of textual …
Current approaches are generally based on the use of different combinations of textual …
Deep learning in image classification using residual network (ResNet) variants for detection of colorectal cancer
This paper investigates a deep learning method in image classification for the detection of
colorectal cancer with ResNet architecture. The exceptional performance of a deep learning …
colorectal cancer with ResNet architecture. The exceptional performance of a deep learning …
Tissue classification and diagnosis of colorectal cancer histopathology images using deep learning algorithms. Is the time ripe for clinical practice implementation?
Colorectal cancer is one of the most prevalent types of cancer, with histopathologic
examination of biopsied tissue samples remaining the gold standard for diagnosis. During …
examination of biopsied tissue samples remaining the gold standard for diagnosis. During …
[HTML][HTML] How deeply to fine-tune a convolutional neural network: a case study using a histopathology dataset
I Kandel, M Castelli - Applied Sciences, 2020 - mdpi.com
Accurate classification of medical images is of great importance for correct disease
diagnosis. The automation of medical image classification is of great necessity because it …
diagnosis. The automation of medical image classification is of great necessity because it …
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 …
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 …
Optimized machine learning for classifying colorectal tissues
Due to numerous deaths, colon cancer treatment and diagnosis are viewed as societal and
financial challenges. The most severe reason for death worldwide is colorectal cancer. The …
financial challenges. The most severe reason for death worldwide is colorectal cancer. The …