Gastroenterology

A Benchmark Dataset of Endoscopic Images and Novel Deep Learning Method to Detect Intestinal Metaplasia and Gastritis Atrophy.

Endoscopy has been routinely used to diagnose stomach diseases including intestinal metaplasia (IM) and gastritis atrophy (GA). Such routine examination usually demands highly skilled radiologists to focus on a single patient with substantial time, causing the following two key challenges: 1) the dependency on the radiologist's experience leading to inconsistent diagnosis results across different ...

Quantitative Mass Spectrometry Imaging Using Multivariate Curve Resolution and Deep Learning: A Case Study.

In the present contribution, a novel approach based on multivariate curve resolution and deep learning (DL) is proposed for quantitative mass spectrometry imaging (MSI) as a potent technique for identifying different compounds and creating their distribution maps in biological tissues without need for sample preparation. As a case study, chlordecone as a carcinogenic pesticide was quantitatively d...

Development and Validation of a Deep Learning Algorithm to Differentiate Colon Carcinoma From Acute Diverticulitis in Computed Tomography Images.

IMPORTANCE: Differentiating between malignant and benign etiology in large-bowel wall thickening on computed tomography (CT) images can be a challengi...

Case of robot-assisted salvage surgery for esophageal cancer with a mediastinal fistula after definitive chemoradiotherapy.

Salvage surgery for esophageal cancer after definitive chemoradiotherapy (dCRT) is effective, but it is associated with a high rate of perioperative c...

Comparison of Operative Time Between Robotic and Laparoscopic Low Anterior Resection for Rectal Cancer:A Systematic Review and Meta-Analysis.

Previous studies have shown that the robotic approach has better perioperative outcomes but longer operative time than the laparoscopic approach for ...

Endoscopic surgery robot that facilitates insertion of the curved colon and ensures positional stability against external forces: K-COLON.

BACKGROUND: Although various endoscopic surgery robots developed in previous studies are versatile and have high lesion accessibility, they have limit...

An AI Approach for Identifying Patients With Cirrhosis.

GOAL: The goal of this study was to evaluate an artificial intelligence approach, namely deep learning, on clinical text in electronic health records ...

Minimally invasive trans-superior articular process percutaneous endoscopic lumbar discectomy with robot assistance.

BACKGROUND: To compare the clinical outcomes of patients with lumbar disc herniation treated with robot-assisted percutaneous endoscopic lumbar discec...

Automated MR Image Prescription of the Liver Using Deep Learning: Development, Evaluation, and Prospective Implementation.

BACKGROUND: There is an unmet need for fully automated image prescription of the liver to enable efficient, reproducible MRI.

The potential role of machine learning in modelling advanced chronic liver disease.

The use of artificial intelligence is rapidly increasing in medicine to support clinical decision making mostly through diagnostic and prediction mode...

Comparison of image quality and pancreatic ductal adenocarcinoma conspicuity between the low-kVp and dual-energy CT reconstructed with deep-learning image reconstruction algorithm.

PURPOSE: To compare the image quality and conspicuity of pancreatic ductal adenocarcinoma (PDAC) between the low-kVp and dual-energy pancreatic protoc...

A Deep Learning Workflow for Mass-Forming Intrahepatic Cholangiocarcinoma and Hepatocellular Carcinoma Classification Based on MRI.

OBJECTIVE: Precise classification of mass-forming intrahepatic cholangiocarcinoma (MF-ICC) and hepatocellular carcinoma (HCC) based on magnetic resona...

Domain generalization improves end-to-end object detection for real-time surgical tool detection.

PURPOSE: Computer assistance for endoscopic surgery depends on knowledge about the contents in an endoscopic scene. An important step of analysing the...

Low-contrast-dose liver CT using low monoenergetic images with deep learning-based denoising for assessing hepatocellular carcinoma: a randomized controlled noninferiority trial.

OBJECTIVE: Low monoenergetic images obtained using noise-reduction techniques may reduce CT contrast media requirements. We aimed to investigate the e...

Robotic operative strategy in locally advanced colon cancer-anatomical precision and the importance of fascial planes - A video vignette.

Usefulness of Breath-Hold Fat-Suppressed T2-Weighted Images With Deep Learning-Based Reconstruction of the Liver: Comparison to Conventional Free-Breathing Turbo Spin Echo.

OBJECTIVES: The aim of this study was to evaluate the usefulness of breath-hold turbo spin echo with deep learning-based reconstruction (BH-DL-TSE) in...

Automated quantitative assessment of pediatric blunt hepatic trauma by deep learning-based CT volumetry.

BACKGROUND: To develop an end-to-end deep learning method for automated quantitative assessment of pediatric blunt hepatic trauma based on contrast-en...

Safe implementation of robotic right colectomy with intracorporeal anastomosis.

The robotic platform can overcome technical difficulties associated with laparoscopic colon surgery. Transitioning from laparoscopic right colectomy w...

Contrast-Enhanced Ultrasound with Deep Learning with Attention Mechanisms for Predicting Microvascular Invasion in Single Hepatocellular Carcinoma.

RATIONALE AND OBJECTIVES: Prediction of microvascular invasion (MVI) status of hepatocellular carcinoma (HCC) holds clinical significance for decision...

Deep learning-based assessment of body composition and liver tumour burden for survival modelling in advanced colorectal cancer.

BACKGROUND: Personalized therapy planning remains a significant challenge in advanced colorectal cancer care, despite extensive research on prognostic...