Panagiotis Korfiatis

发表

Dynamic Susceptibility Contrast-MRI Quantification Software Tool: Development and Evaluation

Bradley J. Erickson, Panagiotis Korfiatis, Timothy L. Kline, 2016, Tomography.

Complete Abdomen and Pelvis Segmentation using U-Net Variant Architecture.

Bradley J Erickson, Panagiotis Korfiatis, Naoki Takahashi, 2020, Medical physics.

NIMG-26COMPARISON OF POST-GADOLINIUM 3D FAST SPIN ECHO IMAGES VERSUS REGISTERED AND SUBTRACTED MPRAGE IMAGES IN GLIOMA PATIENTS

Bradley J. Erickson, Panagiotis Korfiatis, Rickey E. Carter, 2015 .

Toolkits and Libraries for Deep Learning

Bradley J. Erickson, Panagiotis Korfiatis, Zeynettin Akkus, 2017, Journal of Digital Imaging.

High Resolution Medical Image Analysis with Spatial Partitioning pdf

Travis M. Drucker, Noam Shazeer, Panagiotis Korfiatis, 2019, ArXiv.

Residual Deep Convolutional Neural Network Predicts MGMT Methylation Status

Bradley J. Erickson, Panagiotis Korfiatis, Timothy L. Kline, 2017, Journal of Digital Imaging.

Deep Learning in Radiology: Does One Size Fit All?

Bradley J. Erickson, Panagiotis Korfiatis, Timothy L. Kline, 2018, Journal of the American College of Radiology : JACR.

Predictive modeling, machine learning, and statistical issues

Bradley J. Erickson, Panagiotis Korfiatis, Timothy L. Kline, 2019 .

Performance of an Artificial Multi-observer Deep Neural Network for Fully Automated Segmentation of Polycystic Kidneys

Bradley J. Erickson, Panagiotis Korfiatis, Timothy L. Kline, 2017, Journal of Digital Imaging.

Deep Variational Network for High Quality 3D Ultrasound Imaging using Sparse Array

Panagiotis Korfiatis, Ping Gong, Daniel J. Blezek, 2020, 2020 IEEE International Ultrasonics Symposium (IUS).

Computer Aided Diagnosis of Diffuse Lung Disease in Multi-detector CT – Selecting 3D Texture Features

Ioannis Mariolis, Lena Costaridou, Panagiotis Korfiatis, 2010 .

Differences Between Schizophrenic and Normal Subjects Using Network Properties from fMRI

Bradley J. Erickson, Panagiotis Korfiatis, Zeynettin Akkus, 2018, Journal of Digital Imaging.

RIL-Contour: a Medical Imaging Dataset Annotation Tool for and with Deep Learning

Bradley J. Erickson, Panagiotis Korfiatis, Timothy L. Kline, 2019, Journal of Digital Imaging.

Evaluation of a deep learning architecture for MR imaging prediction of ATRX in glioma patients

Bradley J. Erickson, Panagiotis Korfiatis, Timothy L. Kline, 2018, Medical Imaging.

PESSCARA: An Example Infrastructure for Big Data Research

Panagiotis Korfiatis, Bradley Erickson, B. Erickson, 2016 .

Evaluating Multisite rCBV Consistency from DSC-MRI Imaging Protocols and Postprocessing Software Across the NCI Quantitative Imaging Network Sites Using a Digital Reference Object (DRO)

Thomas E. Yankeelov, Chengyue Wu, Mark Muzi, 2019, Tomography.

Interactive segmentation of medical images through fully convolutional neural networks pdf

Daguang Xu, Holger Roth, Bradley J. Erickson, 2019, ArXiv.

Evaluating the Use of rCBV as a Tumor Grade and Treatment Response Classifier Across NCI Quantitative Imaging Network Sites: Part II of the DSC-MRI Digital Reference Object (DRO) Challenge

Thomas E. Yankeelov, Chengyue Wu, Mark Muzi, 2020, Tomography.

Deep Learning Improves the Temporal Reproducibility of Aortic Measurement

Bradley J. Erickson, Panagiotis Korfiatis, William J. Ryan, 2021, Journal of Digital Imaging.

Utilizing magnetization transfer imaging to investigate tissue remodeling in a murine model of autosomal dominant polycystic kidney disease

Bradley J. Erickson, Panagiotis Korfiatis, Timothy L. Kline, 2015, Magnetic resonance in medicine.

Automatic total kidney volume measurement on follow-up magnetic resonance images to facilitate monitoring of autosomal dominant polycystic kidney disease progression.

Bradley J Erickson, Panagiotis Korfiatis, Joshua D. Warner, 2015, Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association.

Quantitative MRI of kidneys in renal disease

Bradley J Erickson, Panagiotis Korfiatis, Sudhakar K Venkatesh, 2018, Abdominal Radiology.

The basics of diffusion and perfusion imaging in brain tumors.

Panagiotis Korfiatis, Bradley Erickson, B. Erickson, 2014, Applied radiology.

Evaluating image denoising methods in myocardial perfusion single photon emission computed tomography (SPECT) imaging

Lena Costaridou, G. S. Panayiotakis, Panagiotis Korfiatis, 2009 .

Image texture features predict renal function decline in patients with autosomal dominant polycystic kidney disease.

Bradley J Erickson, Panagiotis Korfiatis, Douglas Landsittel, 2017, Kidney international.