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Timothy Kline
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2020 – today
- 2024
- [i10]Farhad Maleki, Linda Moy, Reza Forghani, Tapotosh Ghosh, Katie L. Ovens, Steve Langer, Pouria Rouzrokh, Bardia Khosravi, Ali Ganjizadeh, Daniel I. Warren, Roxana Daneshjou, Mana Moassefi, Atlas Haddadi Avval, Susan Sotardi, Neil A. Tenenholtz, Felipe Kitamura, Timothy Kline:
RIDGE: Reproducibility, Integrity, Dependability, Generalizability, and Efficiency Assessment of Medical Image Segmentation Models. CoRR abs/2401.08847 (2024) - [i9]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 abs/2405.01644 (2024) - 2023
- [j8]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): 1770-1781 (2023) - [j7]Mana Moassefi, Pouria Rouzrokh, Gian Marco Conte, Sanaz Vahdati, Tianyuan Fu, Aylin Tahmasebi
Reproducibility of Deep Learning Algorithms Developed for Medical Imaging Analysis: A Systematic Review. J. Imaging Inform. Medicine 36(5): 2306-2312 (2023) - [c5]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: 470-480 - [i8]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 abs/2305.09031 (2023) - [i7]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 abs/2307.14482 (2023) - [i6]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 abs/2308.10372 (2023) - 2022
- [i5]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 abs/2202.01863 (2022) - [i4]Darryl E. Wright, Cole J. Cook, Jason Klug, Panagiotis Korfiatis, Timothy L. Kline:
Reproducibility in medical image radiomic studies: contribution of dynamic histogram binning. CoRR abs/2211.05241 (2022) - [i3]Timothy L. Kline:
Shape Aware Automatic Region-of-Interest Subdivisions. CoRR abs/2212.08810 (2022) - [i2]Timothy L. Kline:
Quantifying and Visualizing Vascular Branching Geometry with Micro-CT: Normalization of Intra- and Inter-Specimen Variations. CoRR abs/2212.10291 (2022) - 2021
- [j6]Adriana V. Gregory, Deema A. Anaam, Andrew J. Vercnocke, Marie E. Edwards, Vicente E. Torres
Semantic Instance Segmentation of Kidney Cysts in MR Images: A Fully Automated 3D Approach Developed Through Active Learning. J. Digit. Imaging 34(4): 773-787 (2021) - [c4]Timothy L. Kline:
Improving Domain Generalization in Segmentation Models with Neural Style Transfer. ISBI 2021: 1324-1328
2010 – 2019
- 2019
- [j5]Kenneth A. Philbrick, Alexander D. Weston, Zeynettin Akkus
RIL-Contour: a Medical Imaging Dataset Annotation Tool for and with Deep Learning. J. Digit. Imaging 32(4): 571-581 (2019) - [c3]Timothy L. Kline:
Segmenting New Image Acquisitions Without Labels. ISBI 2019: 330-333 - 2018
- [c2]Panagiotis Korfiatis, Timothy L. Kline, Bradley J. Erickson:
Evaluation of a deep learning architecture for MR imaging prediction of ATRX in glioma patients. Computer-Aided Diagnosis 2018: 105752G - 2017
- [j4]Bradley J. Erickson, Panagiotis Korfiatis, Zeynettin Akkus
Toolkits and Libraries for Deep Learning. J. Digit. Imaging 30(4): 400-405 (2017) - [j3]Timothy L. Kline
Performance of an Artificial Multi-observer Deep Neural Network for Fully Automated Segmentation of Polycystic Kidneys. J. Digit. Imaging 30(4): 442-448 (2017) - [j2]Panagiotis Korfiatis, Timothy L. Kline, Daniel H. Lachance, Ian F. Parney
Residual Deep Convolutional Neural Network Predicts MGMT Methylation Status. J. Digit. Imaging 30(5): 622-628 (2017) - 2016
- [i1]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 abs/1611.06939 (2016) - 2011
- [j1]Xiao Han, Junguo Bian, Diane R. Eaker, Timothy Kline, Emil Y. Sidky, Erik L. Ritman, Xiaochuan Pan:
Algorithm-Enabled Low-Dose Micro-CT Imaging. IEEE Trans. Medical Imaging 30(3): 606-620 (2011)
2000 – 2009
- 2009
- [c1]Timothy Kline, Erik L. Ritman:
Paths of Least Flow-Resistance: Characterization for the Optimization of Synthetic Tissue Scaffold Design. ISBI 2009: 606-609
Coauthor Index
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