AIMC Topic: Pancreas

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A deep learning framework for pancreas segmentation with multi-atlas registration and 3D level-set.

Medical image analysis Oct 28, 2020
In this paper, we propose and validate a deep learning framework that incorporates both multi-atlas registration and level-set for segmenting pancreas from CT volume images. The proposed segmentation pipeline consists of three stages, namely coarse, ...
Neural Networks, Computer Deep Learning Tomography, X-Ray Computed Image Processing, Computer-Assisted Pancreas
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Improving the slice interaction of 2.5D CNN for automatic pancreas segmentation.

Medical physics Oct 15, 2020
PURPOSE: Volumetric pancreas segmentation can be used in the diagnosis of pancreatic diseases, the research about diabetes and surgical planning. Since manual delineation is time-consuming and laborious, we develop a deep learning-based framework for...
Tomography, X-Ray Computed Image Processing, Computer-Assisted Abdomen Pancreas Neural Networks, Computer
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Utilisation of artificial intelligence for the development of an EUS-convolutional neural network model trained to enhance the diagnosis of autoimmune pancreatitis.

Gut Oct 7, 2020
OBJECTIVE: The diagnosis of autoimmune pancreatitis (AIP) is challenging. Sonographic and cross-sectional imaging findings of AIP closely mimic pancreatic ductal adenocarcinoma (PDAC) and techniques for tissue sampling of AIP are suboptimal. These li...
Carcinoma, Pancreatic Ductal Endosonography Image Interpretation, Computer-Assisted Observer Variation Diagnosis, Differential Pancreatic Neoplasms Area Under Curve Machine Learning Pancreas ROC Curve Autoimmune Pancreatitis Humans Neural Networks, Computer
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Development of a volumetric pancreas segmentation CT dataset for AI applications through trained technologists: a study during the COVID 19 containment phase.

Abdominal radiology (New York) Sep 16, 2020
PURPOSE: To evaluate the performance of trained technologists vis-à-vis radiologists for volumetric pancreas segmentation and to assess the impact of supplementary training on their performance.
Retrospective Studies Tomography, X-Ray Computed Reproducibility of Results Clinical Competence Humans Artificial Intelligence COVID-19 Pancreas Image Processing, Computer-Assisted Radiology Datasets as Topic
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Characterization of patients with advanced chronic pancreatitis using natural language processing of radiology reports.

PloS one Aug 19, 2020
STUDY AIM: To develop and apply a natural language processing algorithm for characterization of patients diagnosed with chronic pancreatitis in a diverse integrated U.S. healthcare system.
Kaplan-Meier Estimate Female Risk Factors Diabetes Complications Pancreatitis, Chronic Aged Adult Humans Image Processing, Computer-Assisted Retrospective Studies Pancreas Sensitivity and Specificity Pancreatic Neoplasms Body Mass Index Tomography, X-Ray Computed Smoking Natural Language Processing Male Proportional Hazards Models Middle Aged
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Deep learning-based pancreas segmentation and station recognition system in EUS: development and validation of a useful training tool (with video).

Gastrointestinal endoscopy May 6, 2020
BACKGROUND AND AIMS: EUS is considered one of the most sensitive modalities for pancreatic cancer detection, but it is highly operator-dependent and the learning curve is steep. In this study, we constructed a system named BP MASTER (pancreaticobilia...
Learning Curve Humans Cross-Over Studies Pancreas Deep Learning Ultrasonography
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Preliminary clinical application of the robot-assisted CT-guided irreversible electroporation ablation for the treatment of pancreatic head carcinoma.

The international journal of medical robotics + computer assisted surgery : MRCAS May 6, 2020
BACKGROUND: To evaluate the feasibility and safety of a robot-guided irreversible electroporation (IRE) ablation system for the treatment of pancreatic head carcinoma.
Pancreatic Neoplasms Robotics Pancreas Electroporation Humans Tomography, X-Ray Computed
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Cellular and Molecular Probing of Intact Human Organs.

Cell Feb 13, 2020
Optical tissue transparency permits scalable cellular and molecular investigation of complex tissues in 3D. Adult human organs are particularly challenging to render transparent because of the accumulation of dense and sturdy molecules in decades-age...
Optical Imaging Eye Aged, 80 and over Kidney Animals Limit of Detection Male Imaging, Three-Dimensional Pancreas Deep Learning Mice Thyroid Gland Staining and Labeling Middle Aged Humans Swine Brain Female
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Deep pancreas segmentation with uncertain regions of shadowed sets.

Magnetic resonance imaging Jan 24, 2020
Pancreas segmentation is a challenging task in medical image analysis especially for the patients with pancreatic cancer. First, the images often have poor contrast and blurred boundaries. Second, there exist large variations in gray scale, texture, ...
Image Processing, Computer-Assisted Uncertainty Fuzzy Logic Reproducibility of Results Magnetic Resonance Imaging Humans Deep Learning Pancreatic Neoplasms Algorithms Pancreas Databases, Factual
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The potential of machine learning to predict postoperative pancreatic fistula based on preoperative, non-contrast-enhanced CT: A proof-of-principle study.

Surgery Nov 11, 2019
BACKGROUND: Postoperative pancreatic fistula remains an unsolved challenge after pancreatoduodenectomy. Important in this regard is the presence of a soft pancreatic texture which is a major risk factor. Advances in machine learning and texture analy...
Middle Aged Female Humans Postoperative Complications Aged Pancreatic Fistula Pancreas Machine Learning Male Positron Emission Tomography Computed Tomography Pancreaticoduodenectomy Proof of Concept Study Retrospective Studies
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