Review on the applications of deep learning in the analysis of gastrointestinal endoscopy images
W Du, N Rao, D Liu, H Jiang, C Luo, Z Li, T Gan… - Ieee …, 2019 - ieeexplore.ieee.org
Gastrointestinal (GI) disease is one of the most common diseases and primarily examined
by GI endoscopy. Recently, deep learning (DL), in particular convolutional neural networks …
by GI endoscopy. Recently, deep learning (DL), in particular convolutional neural networks …
Recent advances in applying machine learning and deep learning to detect upper gastrointestinal tract lesions
The clinical application of a real-time artificial intelligence (AI) image processing system to
diagnose upper gastrointestinal (GI) malignancies remains an experimental research and …
diagnose upper gastrointestinal (GI) malignancies remains an experimental research and …
Detecting and locating gastrointestinal anomalies using deep learning and iterative cluster unification
DK Iakovidis, SV Georgakopoulos… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
This paper proposes a novel methodology for automatic detection and localization of
gastrointestinal (GI) anomalies in endoscopic video frame sequences. Training is performed …
gastrointestinal (GI) anomalies in endoscopic video frame sequences. Training is performed …
A deep CNN model for anomaly detection and localization in wireless capsule endoscopy images
Wireless capsule endoscopy (WCE) is one of the most efficient methods for the examination
of gastrointestinal tracts. Computer-aided intelligent diagnostic tools alleviate the challenges …
of gastrointestinal tracts. Computer-aided intelligent diagnostic tools alleviate the challenges …
Multi-scale context-guided deep network for automated lesion segmentation with endoscopy images of gastrointestinal tract
Accurate lesion segmentation based on endoscopy images is a fundamental task for the
automated diagnosis of gastrointestinal tract (GI Tract) diseases. Previous studies usually …
automated diagnosis of gastrointestinal tract (GI Tract) diseases. Previous studies usually …
Deep transfer learning for automated intestinal bleeding detection in capsule endoscopy imaging
T Ghosh, J Chakareski - Journal of Digital Imaging, 2021 - Springer
Purpose: The objective of this paper was to develop a computer-aided diagnostic (CAD)
tools for automated analysis of capsule endoscopic (CE) images, more precisely, detect …
tools for automated analysis of capsule endoscopic (CE) images, more precisely, detect …
[HTML][HTML] Federated Deep Learning for Wireless Capsule Endoscopy Analysis: Enabling Collaboration Across Multiple Data Centers for Robust Learning of Diverse …
Wireless capsule endoscopy (WCE) is a revolutionary diagnostic method for small bowel
pathology. The manual perusal of the resulting lengthy and redundant videos is …
pathology. The manual perusal of the resulting lengthy and redundant videos is …
[HTML][HTML] Machine learning based small bowel video capsule endoscopy analysis: Challenges and opportunities
Video capsule endoscopy (VCE) is a revolutionary technology for the early diagnosis of
gastric disorders. However, owing to the high redundancy and subtle manifestation of …
gastric disorders. However, owing to the high redundancy and subtle manifestation of …
DSI-Net: Deep synergistic interaction network for joint classification and segmentation with endoscope images
Automatic classification and segmentation of wireless capsule endoscope (WCE) images
are two clinically significant and relevant tasks in a computer-aided diagnosis system for …
are two clinically significant and relevant tasks in a computer-aided diagnosis system for …
Peak-graph-based fast density peak clustering for image segmentation
J Guan, S Li, X He, J Chen - IEEE Signal Processing Letters, 2021 - ieeexplore.ieee.org
Fuzzy c-means (FCM) algorithm as a traditional clustering algorithm for image segmentation
cannot effectively preserve local spatial information of pixels, which leads to poor …
cannot effectively preserve local spatial information of pixels, which leads to poor …