Convolution neural networks for diagnosing colon and lung cancer histopathological images
S Mangal, A Chaurasia, A Khajanchi - arXiv preprint arXiv:2009.03878, 2020 - arxiv.org
Lung and Colon cancer are one of the leading causes of mortality and morbidity in adults.
Histopathological diagnosis is one of the key components to discern cancer type. The aim of …
Histopathological diagnosis is one of the key components to discern cancer type. The aim of …
Automated detection and characterization of colon cancer with deep convolutional neural networks
Colon cancer is a momentous reason for illness and death in people. The conclusive
diagnosis of colon cancer is made through histological examination. Convolutional neural …
diagnosis of colon cancer is made through histological examination. Convolutional neural …
An approach to classify lung and colon cancer of histopathology images using deep feature extraction and an ensemble method
Cancer is a deadly condition brought on by a range of metabolic anomalies and genetic
disorders. Lung and colon cancer in particular is among the leading causes of death and …
disorders. Lung and colon cancer in particular is among the leading causes of death and …
Lung and colon cancer classification using medical imaging: A feature engineering approach
A Hage Chehade, N Abdallah, JM Marion… - … Engineering Sciences in …, 2022 - Springer
Lung and colon cancers lead to a significant portion of deaths. Their simultaneous
occurrence is uncommon, however, in the absence of early diagnosis, the metastasis of …
occurrence is uncommon, however, in the absence of early diagnosis, the metastasis of …
[PDF][PDF] Lung cancer detection using convolutional neural network on histopathological images
BK Hatuwal, HC Thapa - Int. J. Comput. Trends Technol, 2020 - researchgate.net
Lung Cancer is one of the leading life taking cancer worldwide. Early detection and
treatment are crucial for patient recovery. Medical professionals use histopathological …
treatment are crucial for patient recovery. Medical professionals use histopathological …
A machine learning approach to diagnosing lung and colon cancer using a deep learning-based classification framework
The field of Medicine and Healthcare has attained revolutionary advancements in the last
forty years. Within this period, the actual reasons behind numerous diseases were unveiled …
forty years. Within this period, the actual reasons behind numerous diseases were unveiled …
Automated classification of lung cancer types from cytological images using deep convolutional neural networks
A Teramoto, T Tsukamoto, Y Kiriyama… - BioMed research …, 2017 - Wiley Online Library
Lung cancer is a leading cause of death worldwide. Currently, in differential diagnosis of
lung cancer, accurate classification of cancer types (adenocarcinoma, squamous cell …
lung cancer, accurate classification of cancer types (adenocarcinoma, squamous cell …
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 …
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 …
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 …