Inflammatory Bowel Disease

LC-MS/MS-Based Assay for Steroid Profiling in Peripheral and Adrenal Venous Samples for the Subtyping of Primary Aldosteronism.

Given the largely unexplored application of liquid chromatography-tandem mass spectrometry (LC-MS/MS) steroid analysis in primary aldosteronism (PA), we aimed to investigate its diagnostic utility in PA classification and to characterize steroid secretion patterns across PA subtypes. We retrospectively enrolled 67 patients with PA and collected samples from both peripheral and adrenal veins. We pe...

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

Colorectal cancer is a common malignancy and a major health concern in Korea. Although colonoscopy is an effective tool for screening and preventing colorectal cancer through the early detection of pre-cancerous lesions, many factors influence the quality of colonoscopy, including fatigue, experience, inter-observer variation, and human error. Minimizing errors and providing consistent performance...

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

Accurate depth estimation enhances endoscopy navigation and diagnostics, but obtaining ground-truth depth in clinical settings is challenging. Synth...

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

Colonoscopy is vital in the early diagnosis of colorectal polyps. Regular screenings can effectively prevent benign polyps from progressing to CRC. ...

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 treatment options often burdened by adverse effects. Ide...

Artificial intelligence-assisted approach to assessing bowel wall thickness in pediatric inflammatory bowel disease using intestinal ultrasound images.

BACKGROUND AND AIM: Intestinal ultrasound (IUS) potentially spares patients from repeated endoscopies under sedation and eliminates the need for alter...

AI-Assisted Colonoscopy: Polyp Detection and Segmentation using Foundation Models

In colonoscopy, 80% of the missed polyps could be detected with the help of Deep Learning models. In the search for algorithms capable of addressing...

PolypSegTrack: Unified Foundation Model for Colonoscopy Video Analysis

Early detection, accurate segmentation, classification and tracking of polyps during colonoscopy are critical for preventing colorectal cancer. Many...

Vision Language Models versus Machine Learning Models Performance on Polyp Detection and Classification in Colonoscopy Images

Introduction: This study provides a comprehensive performance assessment of vision-language models (VLMs) against established convolutional neural n...

LGPS: A Lightweight GAN-Based Approach for Polyp Segmentation in Colonoscopy Images

Colorectal cancer (CRC) is a major global cause of cancer-related deaths, with early polyp detection and removal during colonoscopy being crucial fo...

3D Densification for Multi-Map Monocular VSLAM in Endoscopy

Multi-map Sparse Monocular visual Simultaneous Localization and Mapping applied to monocular endoscopic sequences has proven efficient to robustly r...

Toward a Human-Centered AI-assisted Colonoscopy System in Australia

While AI-assisted colonoscopy promises improved colorectal cancer screening, its success relies on effective integration into clinical practice, not...

Predicting Treatment Response in Body Dysmorphic Disorder with Interpretable Machine Learning

Body Dysmorphic Disorder (BDD) is a highly prevalent and frequently underdiagnosed condition characterized by persistent, intrusive preoccupations w...

Accurate, Robust, and Scalable Machine Abstraction of Mayo Endoscopic Subscores From Colonoscopy Reports.

BACKGROUND: The Mayo endoscopic subscore (MES) is an important quantitative measure of disease activity in ulcerative colitis. Colonoscopy reports in ...

EndoPBR: Material and Lighting Estimation for Photorealistic Surgical Simulations via Physically-based Rendering

The lack of labeled datasets in 3D vision for surgical scenes inhibits the development of robust 3D reconstruction algorithms in the medical domain....

Test-Time Modality Generalization for Medical Image Segmentation

Generalizable medical image segmentation is essential for ensuring consistent performance across diverse unseen clinical settings. However, existing...

Robust Polyp Detection and Diagnosis through Compositional Prompt-Guided Diffusion Models

Colorectal cancer (CRC) is a significant global health concern, and early detection through screening plays a critical role in reducing mortality. W...

SHADeS: Self-supervised Monocular Depth Estimation Through Non-Lambertian Image Decomposition

Purpose: Visual 3D scene reconstruction can support colonoscopy navigation. It can help in recognising which portions of the colon have been visuali...

Towards Polyp Counting In Full-Procedure Colonoscopy Videos

Automated colonoscopy reporting holds great potential for enhancing quality control and improving cost-effectiveness of colonoscopy procedures. A ma...

Evaluation of risk factors for thromboembolic events in multiple myeloma patients using multiple machine learning models.

Venous thromboembolic events (VTE) is a frequent complication in multiple myeloma (MM) patients, raising mortality. This study aims to use machine lea...