Automated Detection of Pancreatic Cystic Lesions on CT Using Deep Learning

Quantifying Radiology Resident Fatigue: Analysis of Preliminary Reports

(2021) Jan Vosshenrich et al.   RADIOLOGY

Fast and Automated Segmentation for the Three-Directional Multi-Slice Cine Myocardial Velocity Mapping

(2021) Yinzhe Wu et al.   Diagnostics

Robustness of Deep Learning Algorithm to Varying Imaging Conditions in Detecting Low Contrast Objects in Computed Tomography Phantom Images: In Comparison to 12 Radiologists

(2021) Hae Young Kim et al.   Diagnostics

Validation of a fully automated liver segmentation algorithm using multi-scale deep reinforcement learning and comparison versus manual segmentation

(2020) David J. Winkel et al.   EUROPEAN JOURNAL OF RADIOLOGY

AI Augmentation of Radiologist Performance in Distinguishing COVID-19 from Pneumonia of Other Etiology on Chest CT

(2020) Harrison X. Bai et al.   RADIOLOGY

ACR Appropriateness Criteria® Pancreatic Cyst

(2020) Kelly Fábrega-Foster et al.   Journal of the American College of Radiology

Comparative Diagnostic Evaluation with Contrast-Enhanced Ultrasound, Computed Tomography and Magnetic Resonance Imaging in Patients with Pancreatic Cystic Neoplasms

(2020) Ya Sun et al.   Cancer Management and Research

Predicting clinically significant prostate cancer from quantitative image features including compressed sensing radial MRI of prostate perfusion using machine learning: comparison with PI-RADS v2 assessment scores

(2020) David Jean Winkel et al.   Quantitative Imaging in Medicine and Surgery

Automated detection of pulmonary embolism in CT pulmonary angiograms using an AI-powered algorithm

(2020) Thomas Weikert et al.   EUROPEAN RADIOLOGY

CT-Based Radiomics Analysis to Predict Malignancy in Patients with Intraductal Papillary Mucinous Neoplasm (IPMN) of the Pancreas

(2020) David Tobaly et al.   Cancers

nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation

(2020) Fabian Isensee et al.   NATURE METHODS

The present and future of deep learning in radiology

(2019) Luca Saba et al.   EUROPEAN JOURNAL OF RADIOLOGY

Follow-up of Incidentally Detected Pancreatic Cystic Neoplasms: Do Baseline MRI and CT Features Predict Cyst Growth?

(2019) Pallavi Pandey et al.   RADIOLOGY

A Practical Guide to Artificial Intelligence–Based Image Analysis in Radiology

(2019) Thomas Weikert et al.   INVESTIGATIVE RADIOLOGY

Diagnosis and management of pancreatic cystic neoplasms: current evidence and guidelines

(2019) Nadine C. M. van Huijgevoort et al.   Nature Reviews Gastroenterology & Hepatology

Overview and comparison of guidelines for management of pancreatic cystic neoplasms

(2019) Aws Hasan et al.   WORLD JOURNAL OF GASTROENTEROLOGY

Application of Deep Learning to Pancreatic Cancer Detection: Lessons Learned From Our Initial Experience

(2019) Linda C. Chu et al.   Journal of the American College of Radiology

Determining Malignant Potential of Intraductal Papillary Mucinous Neoplasm of the Pancreas: CT versus MRI by Using Revised 2017 International Consensus Guidelines

(2019) Ji Eun Lee et al.   RADIOLOGY

Recurrent Saliency Transformation Network for Tiny Target Segmentation in Abdominal CT Scans

(2019) Lingxi Xie et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Management Guidelines for Pancreatic Cystic Lesions: Should we Adopt or Adapt the Current Roadmaps?

(2019) Filipe Vilas-Boas et al.   Journal of Gastrointestinal and Liver Diseases

Deep Learning in Radiology

(2018) Morgan P. McBee et al.   ACADEMIC RADIOLOGY

A Systematic Review of Fatigue in Radiology: Is It a Problem?

(2018) Nadia Stec et al.   AMERICAN JOURNAL OF ROENTGENOLOGY

European evidence-based guidelines on pancreatic cystic neoplasms

(2018)   GUT

Machine Learning in Medical Imaging

(2018) Maryellen L. Giger   Journal of the American College of Radiology

CT radiomics to predict high-risk intraductal papillary mucinous neoplasms of the pancreas

(2018) Jayasree Chakraborty et al.   MEDICAL PHYSICS

Prospective study on the incidence, prevalence and 5-year pancreatic-related mortality of pancreatic cysts in a population-based study

(2017) Marie-Luise Kromrey et al.   GUT

Pancreatic Cysts

(2017) Jodie A. Barkin et al.   PANCREAS

Revisions of international consensus Fukuoka guidelines for the management of IPMN of the pancreas

(2017) Masao Tanaka et al.   PANCREATOLOGY

Tired in the Reading Room: The Influence of Fatigue in Radiology

(2017) Stephen Waite et al.   Journal of the American College of Radiology

Progress in Fully Automated Abdominal CT Interpretation

(2016) Ronald M. Summers   AMERICAN JOURNAL OF ROENTGENOLOGY

Intraductal papillary mucinous neoplasms of the pancreas with concurrent pancreatic and periampullary neoplasms

(2016) K. Sahora et al.   EJSO

Estimation of the prevalence of asymptomatic pancreatic cysts in the population of San Marino

(2015) Nicola Zanini et al.   PANCREATOLOGY

Increased Error Rates in Preliminary Reports Issued by Radiology Residents Working More Than 10 Consecutive Hours Overnight

(2013) Alexander T. Ruutiainen et al.   ACADEMIC RADIOLOGY

Intraductal Papillary Mucinous Neoplasms of the Pancreas With Distinct Pancreatic Ductal Adenocarcinomas Are Frequently of Gastric Subtype

(2013) Noboru Ideno et al.   ANNALS OF SURGERY

Prediction of invasive carcinoma in branch type intraductal papillary mucinous neoplasms of the pancreas

(2010) Atsushi Kanno et al.   JOURNAL OF GASTROENTEROLOGY

Current Trends in Pancreatic Cystic Neoplasms

(2009) Cristina R. Ferrone   ARCHIVES OF SURGERY

Mucin-Producing Neoplasms of the Pancreas: An Analysis of Distinguishing Clinical and Epidemiologic Characteristics

(2009) Stefano Crippa et al.   Clinical Gastroenterology and Hepatology

Prevalence of Unsuspected Pancreatic Cysts on MDCT

(2008) Thomas A. Laffan et al.   AMERICAN JOURNAL OF ROENTGENOLOGY