Strategies for colorectal cancer screening
U Ladabaum, JA Dominitz, C Kahi, RE Schoen - Gastroenterology, 2020 - Elsevier
The incidence of colorectal cancer (CRC) is increasing worldwide. CRC has high mortality
when detected at advanced stages, yet it is also highly preventable. Given the difficulties in …
when detected at advanced stages, yet it is also highly preventable. Given the difficulties in …
A comprehensive review of deep learning in colon cancer
Deep learning has emerged as a leading machine learning tool in object detection and has
attracted attention with its achievements in progressing medical image analysis …
attracted attention with its achievements in progressing medical image analysis …
[HTML][HTML] Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy
Abstract The Endoscopy Computer Vision Challenge (EndoCV) is a crowd-sourcing initiative
to address eminent problems in develo** reliable computer aided detection and diagnosis …
to address eminent problems in develo** reliable computer aided detection and diagnosis …
[HTML][HTML] Deep learning to find colorectal polyps in colonoscopy: A systematic literature review
Colorectal cancer has a great incidence rate worldwide, but its early detection significantly
increases the survival rate. Colonoscopy is the gold standard procedure for diagnosis and …
increases the survival rate. Colonoscopy is the gold standard procedure for diagnosis and …
Artificial intelligence using convolutional neural networks for real-time detection of early esophageal neoplasia in Barrett's esophagus (with video)
R Hashimoto, J Requa, T Dao, A Ninh, E Tran… - Gastrointestinal …, 2020 - Elsevier
Background and Aims The visual detection of early esophageal neoplasia (high-grade
dysplasia and T1 cancer) in Barrett's esophagus (BE) with white-light and virtual …
dysplasia and T1 cancer) in Barrett's esophagus (BE) with white-light and virtual …
Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge
Polyps are well-known cancer precursors identified by colonoscopy. However, variability in
their size, appearance, and location makes the detection of polyps challenging. Moreover …
their size, appearance, and location makes the detection of polyps challenging. Moreover …
[HTML][HTML] Residual LSTM layered CNN for classification of gastrointestinal tract diseases
Abstract nowadays, considering the number of patients per specialist doctor, the size of the
need for automatic medical image analysis methods can be understood. These systems …
need for automatic medical image analysis methods can be understood. These systems …
Tmd-unet: Triple-unet with multi-scale input features and dense skip connection for medical image segmentation
Deep learning is one of the most effective approaches to medical image processing
applications. Network models are being studied more and more for medical image …
applications. Network models are being studied more and more for medical image …
Automatic polyp recognition in colonoscopy images using deep learning and two-stage pyramidal feature prediction
Polyp recognition in colonoscopy images is crucial for early colorectal cancer detection and
treatment. However, the current manual review requires undivided concentration of the …
treatment. However, the current manual review requires undivided concentration of the …
Real-time polyp detection model using convolutional neural networks
A Nogueira-Rodríguez… - Neural Computing and …, 2022 - Springer
Colorectal cancer is a major health problem, where advances towards computer-aided
diagnosis (CAD) systems to assist the endoscopist can be a promising path to improvement …
diagnosis (CAD) systems to assist the endoscopist can be a promising path to improvement …