Gastroenterology

3D Graph-Connectivity Constrained Network for Hepatic Vessel Segmentation.

Segmentation of hepatic vessels from 3D CT images is necessary for accurate diagnosis and preoperative planning for liver cancer. However, due to the low contrast and high noises of CT images, automatic hepatic vessel segmentation is a challenging task. Hepatic vessels are connected branches containing thick and thin blood vessels, showing an important structural characteristic or a prior: the con...

Automatic Segmentation of Magnetic Resonance Images of Severe Patients with Advanced Liver Cancer and the Molecular Mechanism of Emodin-Induced Apoptosis of HepG2 Cells under the Deep Learning.

To improve the accuracy of clinical diagnosis of severe patients with advanced liver cancer and enhance the effect of chemotherapy treatment, the U-Net model was optimized by introducing the batch normalization (BN) layer and the dropout layer, and the segmentation training and verification of the optimized model were realized by the magnetic resonance (MR) image data. Subsequently, HepG2 cells we...

Robot-assisted completion gastrectomy preserving interposed jejunum in remnant gastric cancer following a proximal gastrectomy reconstructed by jejunal interposition: A case report.

Minimally invasive completion gastrectomy is technically demanding and comprises a variety of procedures depending on the previous operation. We prese...

Da Vinci Single-Port (SP) robotic transverse colectomy for mid-transverse colon cancer.

The role of artificial intelligence in pancreatic surgery: a systematic review.

Artificial intelligence (AI), including machine learning (ML), is being slowly incorporated in medical practice, to provide a more precise and persona...

Deep learning radiomics based on contrast-enhanced ultrasound images for assisted diagnosis of pancreatic ductal adenocarcinoma and chronic pancreatitis.

BACKGROUND: Accurate and non-invasive diagnosis of pancreatic ductal adenocarcinoma (PDAC) and chronic pancreatitis (CP) can avoid unnecessary punctur...

Graph-Based Region and Boundary Aggregation for Biomedical Image Segmentation.

Segmentation is a fundamental task in biomedical image analysis. Unlike the existing region-based dense pixel classification methods or boundary-based...

Human colorectal cancer tissue assessment using optical coherence tomography catheter and deep learning.

Optical coherence tomography (OCT) can differentiate normal colonic mucosa from neoplasia, potentially offering a new mechanism of endoscopic tissue a...

Small intestinal viability assessment using dielectric relaxation spectroscopy and deep learning.

Intestinal ischemia is a serious condition where the surgeon often has to make important but difficult decisions regarding resections and resection ma...

Artificial intelligence (AI) models for the ultrasonographic diagnosis of liver tumors and comparison of diagnostic accuracies between AI and human experts.

BACKGROUND: Ultrasonography (US) is widely used for the diagnosis of liver tumors. However, the accuracy of the diagnosis largely depends on the visua...

Anti-Fatigue and Exercise Performance Improvement Effect of Extract in Mice.

(GT) is a native perennial plant growing across the coastline areas in Taiwan. The current study aimed to examine the efficacy of GT extract in ameli...

A Liver Damage Prediction Using Partial Differential Segmentation with Improved Convolutional Neural Network.

BACKGROUND: The liver is one of the most significant and most essential organs in the human body. It is divided into two granular lobes, one on the ri...

Predicting Colorectal Cancer Using Residual Deep Learning with Nursing Care.

Presently, colorectal cancer is the second most dangerous cancer; around 13% of people have been affected; and it requires an effective image analysis...

Deep-learning model for predicting the survival of rectal adenocarcinoma patients based on a surveillance, epidemiology, and end results analysis.

BACKGROUND: We collected information on patients with rectal adenocarcinoma in the United States from the Surveillance, Epidemiology, and EndResults (...

Combining explainable machine learning, demographic and multi-omic data to inform precision medicine strategies for inflammatory bowel disease.

Inflammatory bowel diseases (IBDs), including ulcerative colitis and Crohn's disease, affect several million individuals worldwide. These diseases are...

Proposing Novel Data Analytics Method for Anatomical Landmark Identification from Endoscopic Video Frames.

BACKGROUND: The anatomical landmarks contain the characteristics that are used to guide the gastroenterologists during the endoscopy. The expert can a...

Deep Learning-Based Classification of Hepatocellular Nodular Lesions on Whole-Slide Histopathologic Images.

BACKGROUND & AIMS: Hepatocellular nodular lesions (HNLs) constitute a heterogeneous group of disorders. Differential diagnosis among these lesions, es...

Effects of Irbesartan and Amlodipine Besylate Tablets on the Intestinal Microflora of Rats With Hypertensive Renal Damage.

The present study aimed to investigate the effects of irbesartan and amlodipine besylate tablets on the intestinal microflora of rats with hypertensi...

Artificial intelligence outperforms standard blood-based scores in identifying liver fibrosis patients in primary care.

For years, hepatologists have been seeking non-invasive methods able to detect significant liver fibrosis. However, no previous algorithm using routin...

Practical Perfusion Quantification in Multispectral Endoscopic Video: Using the Minutes after ICG Administration to Assess Tissue Pathology.

The wide availability of near infrared light sources in interventional medical imaging stacks enables non-invasive quantification of perfusion by usin...