AIMC Topic: Pancreatic Diseases

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Deep Learning Methods in the Imaging of Hepatic and Pancreaticobiliary Diseases.

Journal of clinical gastroenterology
Reports indicate a growing role for artificial intelligence (AI) in the evaluation of pancreaticobiliary and hepatic conditions. A key focus is differentiating between benign and malignant lesions, which is crucial for treatment decisions. AI improve...

Deep learning reconstruction for accelerated 3-D magnetic resonance cholangiopancreatography.

La Radiologia medica
PURPOSE: This study aimed to compare a conventional three-dimensional (3-D) magnetic resonance cholangiopancreatography (MRCP) sequence with a deep learning (DL)-accelerated MRCP sequence (hereafter, MRCP) regarding acquisition time and image quality...

Artificial Intelligence in Pancreatic Imaging: A Systematic Review.

United European gastroenterology journal
The rising incidence of pancreatic diseases, including acute and chronic pancreatitis and various pancreatic neoplasms, poses a significant global health challenge. Pancreatic ductal adenocarcinoma (PDAC) for example, has a high mortality rate due to...

The Role of Artificial Intelligence for Advanced Endoscopy.

Gastrointestinal endoscopy clinics of North America
Artificial intelligence (AI) application in gastroenterology has grown in the last decade and continues to evolve very rapidly. Early promising results have opened the door to explore its potential application to advanced endoscopy (AE). The aim of t...

Artificial intelligence in pancreaticobiliary endoscopy: Current applications and future directions.

Journal of digestive diseases
Pancreaticobiliary endoscopy is an essential tool for diagnosing and treating pancreaticobiliary diseases. However, it does not fully meet clinical needs, which presents challenges such as significant difficulty in operation and risks of missed diagn...

Deep Learning Reconstruction for Enhanced Resolution and Image Quality in Breath-Hold MRCP: A Preliminary Study.

Journal of computer assisted tomography
OBJECTIVE: This preliminary study aims to assess the image quality of enhanced-resolution deep learning reconstruction (ER-DLR) in magnetic resonance cholangiopancreatography (MRCP) and compare it with non-ER-DLR MRCP images.

Enhancing detection of various pancreatic lesions on endoscopic ultrasound through artificial intelligence: a basis for computer-aided detection systems.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: Endoscopic ultrasound (EUS) is the most sensitive method for evaluation of pancreatic lesions but is limited by significant operator dependency. Artificial intelligence (AI), in the form of computer-aided detection (CADe) systems,...

Large-scale multi-center CT and MRI segmentation of pancreas with deep learning.

Medical image analysis
Automated volumetric segmentation of the pancreas on cross-sectional imaging is needed for diagnosis and follow-up of pancreatic diseases. While CT-based pancreatic segmentation is more established, MRI-based segmentation methods are understudied, la...

Current and Emerging Applications of Artificial Intelligence (AI) in the Management of Pancreatobiliary (PB) disorders.

Current gastroenterology reports
PURPOSEĀ OF REVIEW: In this review, we aim to summarize the existing literature and future directions on the use of artificial intelligence (AI) for the diagnosis and treatment of PB (pancreaticobiliary) disorders. RECENT FINDINGS: AI models have been...

Deep Learning Reconstruction of Prospectively Accelerated MRI of the Pancreas: Clinical Evaluation of Shortened Breath-Hold Examinations With Dixon Fat Suppression.

Investigative radiology
OBJECTIVE: Deep learning (DL)-enabled magnetic resonance imaging (MRI) reconstructions can enable shortening of breath-hold examinations and improve image quality by reducing motion artifacts. Prospective studies with DL reconstructions of accelerate...