Timothy L. Kline

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 17

Top Topics

Automatic Segmentation

Dice Similarity Coefficient

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)
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, Adriana V. Gregory, Deema A. Anaam, Sepideh Yadollahi, Sumana Ramanathan, Kafayat A. Oyemade, Reem Alsibai, Heather Holmes, Harrison C. Gottlich, Cherie-Akilah G. Browne, Sarah L. Cohen Rassier, Isabel Green, Elizabeth A. Stewart, Hiroaki Takahashi, Bohyun Kim, Shannon Laughlin-Tommaso, Timothy L. Kline
Developing a Machine Learning-Based Clinical Decision Support Tool for Uterine Tumor Imaging. CoRR (2023)
Timothy L. Kline, Felipe Kitamura, Ian Pan, Amine M. Korchi, Neil A. Tenenholtz, Linda Moy, Judy Wawira Gichoya, Igor Santos, Steven Blumer, Misha Ysabel Hwang, Kim-Ann Git, Abishek Shroff, Elad Walach, George Shih, Steve Langer
Best Practices and Scoring System on Reviewing A.I. based Medical Imaging Papers: Part 1 Classification. CoRR (2022)
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)
Timothy L. Kline
Quantifying and Visualizing Vascular Branching Geometry with Micro-CT: Normalization of Intra- and Inter-Specimen Variations. CoRR (2022)
Timothy L. Kline
Shape Aware Automatic Region-of-Interest Subdivisions. CoRR (2022)
Timothy L. Kline
Improving Domain Generalization in Segmentation Models with Neural Style Transfer. ISBI (2021)
Adriana V. Gregory, Deema A. Anaam, Andrew J. Vercnocke, Marie E. Edwards, Vicente E. Torres, Peter C. Harris, Bradley J. Erickson, Timothy L. Kline
Semantic Instance Segmentation of Kidney Cysts in MR Images: A Fully Automated 3D Approach Developed Through Active Learning. J. Digit. Imaging 34 (4) (2021)
Timothy L. Kline
Segmenting New Image Acquisitions Without Labels. ISBI (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)
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)
Zeynettin Akkus, Issa Ali, Jirí Sedlár, Timothy L. Kline, Jay P. Agrawal, Ian F. Parney, Caterina Giannini, Bradley J. Erickson
Predicting 1p19q Chromosomal Deletion of Low-Grade Gliomas from MR Images using Deep Learning. CoRR (2016)