Deep transfer learning from ordinary to capsule esophagogastroduodenoscopy for image quality controlling
Y Zhang, K Zhang, Y Ding, S Liu, M Wang… - Engineering …, 2024 - Wiley Online Library
Quality controlling for capsule endoscopic images can be completed with the assistance of
artificial intelligence, but the labeling process is time‐consuming. Domain adaption is a …
artificial intelligence, but the labeling process is time‐consuming. Domain adaption is a …
Anatomical sites identification in both ordinary and capsule gastroduodenoscopy via deep learning
K Zhang, Y Zhang, Y Ding, M Wang, P Bai… - … Signal Processing and …, 2024 - Elsevier
Anatomical sites recognition is a basic requirement for gastroenterologists. But there is not a
unified framework for anatomical sites identification in both ordinary and capsule …
unified framework for anatomical sites identification in both ordinary and capsule …
Zoom in lesions for better diagnosis: Attention guided deformation network for wce image classification
Wireless capsule endoscopy (WCE) is a novel imaging tool that allows noninvasive
visualization of the entire gastrointestinal (GI) tract without causing discomfort to patients …
visualization of the entire gastrointestinal (GI) tract without causing discomfort to patients …
AdaSAN: Adaptive cosine similarity self-attention network for gastrointestinal endoscopy image classification
Q Zhao, W Yang, Q Liao - 2021 IEEE 18th International …, 2021 - ieeexplore.ieee.org
Wireless capsule endoscopy plays an important role in the examination of gastrointestinal
diseases. However, the large number of medical images produced by endoscopy makes it a …
diseases. However, the large number of medical images produced by endoscopy makes it a …
A CNN-based blind denoising method for endoscopic images
S Zou, M Long, X Wang, X Xie, G Li… - 2019 IEEE Biomedical …, 2019 - ieeexplore.ieee.org
The quality of images captured by wireless capsule endoscopy (WCE) is key for doctors to
diagnose diseases of gastrointestinal (GI) tract. However, there exist many low-quality …
diagnose diseases of gastrointestinal (GI) tract. However, there exist many low-quality …
[HTML][HTML] Reduced detection rate of artificial intelligence in images obtained from untrained endoscope models and improvement using domain adaptation algorithm
A training dataset that is limited to a specific endoscope model can overfit artificial
intelligence (AI) to its unique image characteristics. The performance of the AI may degrade …
intelligence (AI) to its unique image characteristics. The performance of the AI may degrade …
Using the triplet loss for domain adaptation in WCE
Abstract Wireless Capsule Endoscopy (WCE) is a minimally-invasive procedure that, based
on a vitamin-size camera that is swallowed by the patient, allows the visualization of the …
on a vitamin-size camera that is swallowed by the patient, allows the visualization of the …
A convolutional neural network with meta-feature learning for wireless capsule endoscopy image classification
Abstract Purpose Wireless Capsule Endoscopy is a widely used method for gastrointestinal
tract inspection. Automatic gastrointestinal abnormality detection systems face a key issue of …
tract inspection. Automatic gastrointestinal abnormality detection systems face a key issue of …
Convolutional‐capsule network for gastrointestinal endoscopy image classification
Automated diagnosis of digestive tract diseases from gastrointestinal endoscopy images is
of high importance for improving the diagnosis accuracy and efficiency. The current …
of high importance for improving the diagnosis accuracy and efficiency. The current …
Triple ANet: Adaptive abnormal-aware attention network for WCE image classification
Accurate detection of abnormal regions in Wireless Capsule Endoscopy (WCE) images is
crucial for early intestine cancer diagnosis and treatment, while it still remains challenging …
crucial for early intestine cancer diagnosis and treatment, while it still remains challenging …