Gastroenterology

WEO Newsletter: The Impact of Artificial Intelligence on Gastrointestinal Endoscopy.

Investigating Zero-Shot Diagnostic Pathology in Vision-Language Models with Efficient Prompt Design

Vision-language models (VLMs) have gained significant attention in computational pathology due to ...

Glucagon and insulin production in pancreatic cells modeled using Petri nets and Boolean networks

Diabetes is a civilization chronic disease characterized by a constant elevated concentration of g...

eNCApsulate: NCA for Precision Diagnosis on Capsule Endoscopes

Wireless Capsule Endoscopy is a non-invasive imaging method for the entire gastrointestinal tract,...

Dynamic Contextual Attention Network: Transforming Spatial Representations into Adaptive Insights for Endoscopic Polyp Diagnosis

Colorectal polyps are key indicators for early detection of colorectal cancer. However, traditiona...

Hybrid Approach Combining Ultrasound and Blood Test Analysis with a Voting Classifier for Accurate Liver Fibrosis and Cirrhosis Assessment

Liver cirrhosis is an insidious condition involving the substitution of normal liver tissue with f...

Boosting 3D Liver Shape Datasets with Diffusion Models and Implicit Neural Representations

While the availability of open 3D medical shape datasets is increasing, offering substantial benef...

Artificial intelligence in liver cancer surgery: Predicting success before the first incision.

Advancements in machine learning have revolutionized preoperative risk assessment. In this article, ...

Machine learning algorithms reveal gut microbiota signatures associated with chronic hepatitis B-related hepatic fibrosis.

BACKGROUND: Hepatic fibrosis (HF) represents a pivotal stage in the progression and potential revers...

HepatoGEN: Generating Hepatobiliary Phase MRI with Perceptual and Adversarial Models

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) plays a crucial role in the detecti...

[Role of Artificial Intelligence in Improving Quality of Colonoscopy].

Colorectal cancer is a common malignancy and a major health concern in Korea. Although colonoscopy i...

[Small bowel video keyframe retrieval based on multi-modal contrastive learning].

Retrieving keyframes most relevant to text from small intestine videos with given labels can efficie...

Occlusion-Aware Self-Supervised Monocular Depth Estimation for Weak-Texture Endoscopic Images

We propose a self-supervised monocular depth estimation network tailored for endoscopic scenes, ai...

Anatomy-constrained modelling of image-derived input functions in dynamic PET using multi-organ segmentation

Accurate kinetic analysis of [$^{18}$F]FDG distribution in dynamic positron emission tomography (P...

PPS-Ctrl: Controllable Sim-to-Real Translation for Colonoscopy Depth Estimation

Accurate depth estimation enhances endoscopy navigation and diagnostics, but obtaining ground-trut...

Landmark-Free Preoperative-to-Intraoperative Registration in Laparoscopic Liver Resection

Liver registration by overlaying preoperative 3D models onto intraoperative 2D frames can assist s...

FocusNet: Transformer-enhanced Polyp Segmentation with Local and Pooling Attention

Colonoscopy is vital in the early diagnosis of colorectal polyps. Regular screenings can effective...

Attention GhostUNet++: Enhanced Segmentation of Adipose Tissue and Liver in CT Images

Accurate segmentation of abdominal adipose tissue, including subcutaneous (SAT) and visceral adipo...

Rapid pathologic grading-based diagnosis of esophageal squamous cell carcinoma Raman spectroscopy and a deep learning algorithm.

BACKGROUND: Esophageal squamous cell carcinoma is a major histological subtype of esophageal cancer....

Predicting ulcer in H&E images of inflammatory bowel disease using domain-knowledge-driven graph neural network

Inflammatory bowel disease (IBD) involves chronic inflammation of the digestive tract, with treatm...

Benchmarking Multi-Organ Segmentation Tools for Multi-Parametric T1-weighted Abdominal MRI

The segmentation of multiple organs in multi-parametric MRI studies is critical for many applicati...