Panagiotis Korfiatis

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 16

Top Topics

Automatic Segmentation

Top Venues

J. Digit. Imaging

Medical Imaging: Computer-Aided Diagnosis

Publications

Peilong Wang, Timothy L. Kline, Andy D. Missert, Cole J. Cook, Matthew R. Callstrom, Alex Chan, Robert P. Hartman, Zachary S. Kelm, Panagiotis Korfiatis
A Classification-Based Adaptive Segmentation Pipeline: Feasibility Study Using Polycystic Liver Disease and Metastases from Colorectal Cancer CT Images. CoRR (2024)
Weiguo Cao, Benjamin Howe, Nicholas Rhodes, Sumana Ramanathan, Panagiotis Korfiatis, Kimberly Amrami, Robert Spinner, Timothy Kline
A Texture Neural Network to Predict the Abnormal Brachial Plexus from Routine Magnetic Resonance Imaging. MICCAI (8) (2023)
Harrison C. Gottlich, Panagiotis Korfiatis, Adriana V. Gregory, Timothy L. Kline
AI in the Loop - Functionalizing Fold Performance Disagreement to Monitor Automated Medical Image Segmentation Pipelines. CoRR (2023)
Timothy L. Kline, Sumana Ramanathan, Harrison C. Gottlich, Panagiotis Korfiatis, Adriana V. Gregory
Role of Image Acquisition and Patient Phenotype Variations in Automatic Segmentation Model Generalization. CoRR (2023)
Harrison C. Gottlich, Adriana V. Gregory, Vidit Sharma, Abhinav Khanna, Amr U. Moustafa, Christine M. Lohse, Theodora A. Potretzke, Panagiotis Korfiatis, Aaron M. Potretzke, Aleksandar Denic, Andrew D. Rule, Naoki Takahashi, Bradley J. Erickson, Bradley C. Leibovich, Timothy L. Kline
Effect of Dataset Size and Medical Image Modality on Convolutional Neural Network Model Performance for Automated Segmentation: A CT and MR Renal Tumor Imaging Study. J. Digit. Imaging 36 (4) (2023)
Darryl E. Wright, Cole Cook, Jason Klug, Panagiotis Korfiatis, Timothy L. Kline
Reproducibility in medical image radiomic studies: contribution of dynamic histogram binning. CoRR (2022)
Alex Bratt, Daniel J. Blezek, William J. Ryan, Kenneth A. Philbrick, Prabhakar Rajiah, Yasmeen K. Tandon, Lara A. Walkoff, Jason C. Cai, Emily N. Sheedy, Panagiotis Korfiatis, Eric E. Williamson, Bradley J. Erickson, Jeremy D. Collins
Deep Learning Improves the Temporal Reproducibility of Aortic Measurement. J. Digit. Imaging 34 (5) (2021)
Daniel J. Blezek, Lonny Olson-Williams, Andrew Missert, Panagiotis Korfiatis
AI Integration in the Clinical Workflow. J. Digit. Imaging 34 (6) (2021)
Le Hou, Youlong Cheng, Noam Shazeer, Niki Parmar, Yeqing Li, Panagiotis Korfiatis, Travis M. Drucker, Daniel J. Blezek, Xiaodan Song
High Resolution Medical Image Analysis with Spatial Partitioning. CoRR (2019)
Tomas Sakinis, Fausto Milletari, Holger Roth, Panagiotis Korfiatis, Petro M. Kostandy, Kenneth Philbrick, Zeynettin Akkus, Ziyue Xu, Daguang Xu, Bradley J. Erickson
Interactive segmentation of medical images through fully convolutional neural networks. CoRR (2019)
Kenneth A. Philbrick, Alexander D. Weston, Zeynettin Akkus, Timothy L. Kline, Panagiotis Korfiatis, Tomas Sakinis, Petro M. Kostandy, Arunnit Boonrod, Atefeh Zeinoddini, Naoki Takahashi, Bradley J. Erickson
RIL-Contour: a Medical Imaging Dataset Annotation Tool for and with Deep Learning. J. Digit. Imaging 32 (4) (2019)
Panagiotis Korfiatis, Timothy L. Kline, Bradley J. Erickson
Evaluation of a deep learning architecture for MR imaging prediction of ATRX in glioma patients. Medical Imaging: Computer-Aided Diagnosis (2018)
Youngoh Bae, Kunaraj Kumarasamy, Issa Ali, Panagiotis Korfiatis, Zeynettin Akkus, Bradley J. Erickson
Differences Between Schizophrenic and Normal Subjects Using Network Properties from fMRI. J. Digit. Imaging 31 (2) (2018)
Bradley J. Erickson, Panagiotis Korfiatis, Zeynettin Akkus, Timothy Kline, Kenneth Philbrick
Toolkits and Libraries for Deep Learning. J. Digit. Imaging 30 (4) (2017)
Timothy L. Kline, Panagiotis Korfiatis, Marie E. Edwards, Jaime D. Blais, Frank S. Czerwiec, Peter C. Harris, Bernard F. King, Vicente E. Torres, Bradley J. Erickson
Performance of an Artificial Multi-observer Deep Neural Network for Fully Automated Segmentation of Polycystic Kidneys. J. Digit. Imaging 30 (4) (2017)
Panagiotis Korfiatis, Timothy L. Kline, Daniel H. Lachance, Ian F. Parney, Jan C. Buckner, Bradley J. Erickson
Residual Deep Convolutional Neural Network Predicts MGMT Methylation Status. J. Digit. Imaging 30 (5) (2017)