Kenneth Philbrick

According to our database, Kenneth Philbrick authored at least 8 papers between 2017 and 2021.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2021

Deep Learning Improves the Temporal Reproducibility of Aortic Measurement.

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

J. Digit. Imaging, 2021

SOUP-GAN: Super-Resolution MRI Using Generative Adversarial Networks.

Kuan Zhang, Haoji Hu, Kenneth Philbrick, Gian Marco Conte, Joseph D. Sobek, Pouria Rouzrokh, Bradley J. Erickson

CoRR, 2021

2020

Robust brain extraction tool for CT head images.

Zeynettin Akkus, Petro M. Kostandy, Kenneth A. Philbrick, Bradley J. Erickson

Neurocomputing, 2020

2019

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

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

J. Digit. Imaging, 2019

Interactive segmentation of medical images through fully convolutional neural networks.

Tomas Sakinis, Fausto Milletari, Holger Roth, Panagiotis Korfiatis, Petro M. Kostandy, Kenneth Philbrick, Zeynettin Akkus, Ziyue Xu, Daguang Xu, Bradley J. Erickson

CoRR, 2019

Reduction of unnecessary thyroid biopsies using deep learning.

Zeynettin Akkus, Arunnit Boonrod, Mahfuzur R. Siddiquee, Kenneth A. Philbrick, Marius N. Stan, Regina M. Castro, Dana Erickson, Matthew R. Callstrom, Bradley J. Erickson

Proceedings of the Medical Imaging 2019: Image Processing, 2019

2018

Extraction of brain tissue from CT head images using fully convolutional neural networks.

Zeynettin Akkus, Petro M. Kostandy, Kenneth A. Philbrick, Bradley J. Erickson

Proceedings of the Medical Imaging 2018: Image Processing, 2018

2017

Toolkits and Libraries for Deep Learning.

Bradley J. Erickson, Panagiotis Korfiatis, Zeynettin Akkus, Timothy Kline, Kenneth Philbrick

J. Digit. Imaging, 2017