Gastroenterology

Latest AI and machine learning research in gastroenterology for healthcare professionals.

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Diff4MMLiTS: Advanced Multimodal Liver Tumor Segmentation via Diffusion-Based Image Synthesis and Alignment

Multimodal learning has been demonstrated to enhance performance across various clinical tasks, ow...

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies

Hepatic vessels in computed tomography scans often suffer from image fragmentation and noise inter...

Image detection method for multi-category lesions in wireless capsule endoscopy based on deep learning models.

BACKGROUND: Wireless capsule endoscopy (WCE) has become an important noninvasive and portable tool f...

Dec 2024 39735271
ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation

The growing need for accurate and efficient 3D identification of tumors, particularly in liver seg...

MNet-SAt: A Multiscale Network with Spatial-enhanced Attention for Segmentation of Polyps in Colonoscopy

Objective: To develop a novel deep learning framework for the automated segmentation of colonic po...

Transformer-Based Wireless Capsule Endoscopy Bleeding Tissue Detection and Classification

Informed by the success of the transformer model in various computer vision tasks, we design an en...

[Design and research of a pneumatic soft intestine robot imitating the inchworm].

In order to seek a patient friendly and low-cost intestinal examination method, a structurally simpl...

Dec 2024 40000202
[Research progress on endoscopic image diagnosis of gastric tumors based on deep learning].

Gastric tumors are neoplastic lesions that occur in the stomach, posing a great threat to human heal...

Dec 2024 40000222
ClassifyViStA:WCE Classification with Visual understanding through Segmentation and Attention

Gastrointestinal (GI) bleeding is a serious medical condition that presents significant diagnostic...

MRANet: A Modified Residual Attention Networks for Lung and Colon Cancer Classification

Lung and colon cancers are predominant contributors to cancer mortality. Early and accurate diagno...

V$^2$-SfMLearner: Learning Monocular Depth and Ego-motion for Multimodal Wireless Capsule Endoscopy

Deep learning can predict depth maps and capsule ego-motion from capsule endoscopy videos, aiding ...

Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image with Two-Stage Model

Accurate detection and segmentation of gastrointestinal bleeding are critical for diagnosing disea...

Automated Bleeding Detection and Classification in Wireless Capsule Endoscopy with YOLOv8-X

Gastrointestinal (GI) bleeding, a critical indicator of digestive system disorders, re quires effi...

SegCol Challenge: Semantic Segmentation for Tools and Fold Edges in Colonoscopy data

Colorectal cancer (CRC) remains a leading cause of cancer-related deaths worldwide, with polyp rem...

MiniGPT-Pancreas: Multimodal Large Language Model for Pancreas Cancer Classification and Detection

Problem: Pancreas radiological imaging is challenging due to the small size, blurred boundaries, a...

Read Like a Radiologist: Efficient Vision-Language Model for 3D Medical Imaging Interpretation

Recent medical vision-language models (VLMs) have shown promise in 2D medical image interpretation...

Developing a Predictive Model for Metastatic Potential in Pancreatic Neuroendocrine Tumor.

CONTEXT: Pancreatic neuroendocrine tumors (PNETs) exhibit a wide range of behavior from localized di...

Dec 2024 38817124
Machine Learning Reveals the Contribution of Lipoproteins to Liver Triglyceride Content and Inflammation.

CONTEXT: Metabolic dysfunction-associated steatotic liver disease (MASLD) is currently the most comm...

Dec 2024 38833012
a2z-1 for Multi-Disease Detection in Abdomen-Pelvis CT: External Validation and Performance Analysis Across 21 Conditions

We present a comprehensive evaluation of a2z-1, an artificial intelligence (AI) model designed to ...

Thermodynamics-informed graph neural networks for real-time simulation of digital human twins

The growing importance of real-time simulation in the medical field has exposed the limitations an...

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