AIMC Topic: Pancreatic Diseases

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A Comparison of CT-Based Pancreatic Segmentation Deep Learning Models.

Academic radiology
RATIONALE AND OBJECTIVES: Pancreas segmentation accuracy at CT is critical for the identification of pancreatic pathologies and is essential for the development of imaging biomarkers. Our objective was to benchmark the performance of five high-perfor...

Application of artificial intelligence in pancreas endoscopic ultrasound imaging- A systematic review.

Computer methods and programs in biomedicine
The pancreas is a vital organ in digestive system which has significant health implications. It is imperative to evaluate and identify malignant pancreatic lesions promptly in light of the high mortality rate linked to such malignancies. Endoscopic U...

On the prediction of SAV transmission among Norwegian aquaculture sites.

Preventive veterinary medicine
Pancreas Disease (PD) is a viral disease that affects Atlantic salmon (Salmo salar) in Norwegian, Scottish and Irish aquaculture. It is caused by salmonid alphavirus (SAV) and represents a significant problem in salmonid farming. Infection with SAV l...

[Current CT developments in imaging of pancreatic diseases].

Radiologie (Heidelberg, Germany)
BACKGROUND: Diseases of the pancreas are often diagnosed late and can have fatal consequences for patients.

Artificial intelligence assisted whole organ pancreatic fat estimation on magnetic resonance imaging and correlation with pancreas attenuation on computed tomography.

Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]
BACKGROUND: Fatty pancreas is associated with inflammatory and neoplastic pancreatic diseases. Magnetic resonance imaging (MRI) is the diagnostic modality of choice for measuring pancreatic fat. Measurements typically use regions of interest limited ...

Deep learning for pancreatic diseases based on endoscopic ultrasound: A systematic review.

International journal of medical informatics
BACKGROUND AND AIMS: Endoscopic ultrasonography (EUS) is one of the main examinations in pancreatic diseases. A series of the studies reported the application of deep learning (DL)-assisted EUS in the diagnosis of pancreatic diseases. This systematic...

Rapid 3D breath-hold MR cholangiopancreatography using deep learning-constrained compressed sensing reconstruction.

European radiology
OBJECTIVES: To compare the image quality of three-dimensional breath-hold magnetic resonance cholangiopancreatography with deep learning-based compressed sensing reconstruction (3D DL-CS-MRCP) to those of 3D breath-hold MRCP with compressed sensing (...

Breath-hold 3D magnetic resonance cholangiopancreatography at 1.5 T using a deep learning-based noise-reduction approach: Comparison with the conventional respiratory-triggered technique.

European journal of radiology
OBJECTIVES: To assess the image quality of conventional respiratory-triggered 3-dimentional (3D) magnetic resonance cholangiopancreatography (Resp-MRCP) and breath-hold 3D MRCP (BH-MRCP) with and without denoising procedure using deep learning-based ...

Artificial intelligence: a critical review of current applications in pancreatic imaging.

Japanese journal of radiology
The applications of artificial intelligence (AI), including machine learning and deep learning, in the field of pancreatic disease imaging are rapidly expanding. AI can be used for the detection of pancreatic ductal adenocarcinoma and other pancreati...

Performance of deep learning for differentiating pancreatic diseases on contrast-enhanced magnetic resonance imaging: A preliminary study.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to evaluate the ability of deep learning to differentiate pancreatic diseases on contrast-enhanced magnetic resonance (MR) images with the aid of generative adversarial network (GAN).