A Systematic Review on Detection of Gastric Cancer in Endoscopic Imaging System in Artificial Intelligence Applications
K Pooja, R Kishore Kanna - … Conference on Data & Information Sciences, 2023 - Springer
Artificial intelligence and disease detection go hand in hand. Convolutional neural networks,
a significant area of artificial intelligence applications, are crucial in the detection of stomach …
a significant area of artificial intelligence applications, are crucial in the detection of stomach …
[HTML][HTML] Semantic segmentation of digestive abnormalities from wce images by using attresu-net architecture
Colorectal cancer is one of the most common malignancies and the leading cause of cancer
death worldwide. Wireless capsule endoscopy is currently the most frequent method for …
death worldwide. Wireless capsule endoscopy is currently the most frequent method for …
ViTCA-Net: a framework for disease detection in video capsule endoscopy images using a vision transformer and convolutional neural network with a specific …
Video capsule endoscopy (VCE) is a non-invasive procedure to examine the human bowel.
The VCE technology generates thousands of images from different parts of the …
The VCE technology generates thousands of images from different parts of the …
Conv-vit: Feature fusion-based detection of gastrointestinal abnormalities using cnn and vit in wce images
Vision Transformer (ViT) and its variants have gained significant prominence in computer
vision due to their exceptional performance across various tasks. However, ViTs are data …
vision due to their exceptional performance across various tasks. However, ViTs are data …
A new hybrid approach for pneumonia detection using chest X-rays based on ACNN-LSTM and attention mechanism
Pneumonia is a serious inflammatory disease that causes lung ulcers, and it is one of the
leading reasons for pediatric death in the world. Chest X-rays are perhaps the most …
leading reasons for pediatric death in the world. Chest X-rays are perhaps the most …
Advancements in Polyp Detection: A Developed Single Shot Multibox Detector Approach
The significant challenge in detecting polyps in wireless capsule endoscopy and
colonoscopy images lies in identifying the small ones. This detection task exhibits variability …
colonoscopy images lies in identifying the small ones. This detection task exhibits variability …
Endoscopic Image Analysis for Gastrointestinal Tract Disease Diagnosis Using Nature Inspired Algorithm With Deep Learning Approach
A Alruban, E Alabdulkreem, MM Eltahir… - IEEE …, 2023 - ieeexplore.ieee.org
Endoscopic image analysis has played a pivotal function in the diagnosis and management
of gastrointestinal (GI) tract diseases. Gastrointestinal endoscopy is a medical procedure …
of gastrointestinal (GI) tract diseases. Gastrointestinal endoscopy is a medical procedure …
Local Lesion Generation is Effective for Capsule Endoscopy Image Data Augmentation in a Limited Data Setting
AB Chłopowiec, AR Chłopowiec, K Galus… - arXiv preprint arXiv …, 2024 - arxiv.org
Limited medical imaging datasets challenge deep learning models by increasing risks of
overfitting and reduced generalization, particularly in Generative Adversarial Networks …
overfitting and reduced generalization, particularly in Generative Adversarial Networks …
GastroSegNet: Polyp Segmentation using Colonoscopic Images Based on AttentionU-net Architecture
Colorectal cancer is the main reason for mortality from cancer globally. One of the most
popular methods for spotting precancerous gut illnesses right now is a colonoscopy. As a …
popular methods for spotting precancerous gut illnesses right now is a colonoscopy. As a …
AttDenseUnet: Segmentation of Polyps from Colonoscopic Images Based on Attention-DenseNet-Unet Architecture
Globally, colorectal cancer is the primary cause of cancer-related death. Colonoscopy is
currently one of the most common ways to identify precancerous gastrointestinal disorders …
currently one of the most common ways to identify precancerous gastrointestinal disorders …