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Timothy L Kline, PhD
Timothy L Kline, PhD
Verified email at mayo.edu
Title
Cited by
Cited by
Year
Machine learning for medical imaging
BJ Erickson, P Korfiatis, Z Akkus, TL Kline
radiographics 37 (2), 505-515, 2017
18222017
Automated abdominal segmentation of CT scans for body composition analysis using deep learning
AD Weston, P Korfiatis, TL Kline, KA Philbrick, P Kostandy, T Sakinis, ...
Radiology 290 (3), 669-679, 2019
3432019
Toolkits and libraries for deep learning
BJ Erickson, P Korfiatis, Z Akkus, T Kline, K Philbrick
Journal of digital imaging 30, 400-405, 2017
2242017
Residual deep convolutional neural network predicts MGMT methylation status
P Korfiatis, TL Kline, DH Lachance, IF Parney, JC Buckner, BJ Erickson
Journal of digital imaging 30, 622-628, 2017
2142017
Algorithm-enabled low-dose micro-CT imaging
X Han, J Bian, DR Eaker, TL Kline, EY Sidky, EL Ritman, X Pan
IEEE transactions on medical imaging 30 (3), 606-620, 2010
1812010
MRI texture features as biomarkers to predict MGMT methylation status in glioblastomas
P Korfiatis, TL Kline, L Coufalova, DH Lachance, IF Parney, RE Carter, ...
Medical physics 43 (6Part1), 2835-2844, 2016
1762016
Performance of an artificial multi-observer deep neural network for fully automated segmentation of polycystic kidneys
TL Kline, P Korfiatis, ME Edwards, JD Blais, FS Czerwiec, PC Harris, ...
Journal of digital imaging 30, 442-448, 2017
1602017
Deep learning in radiology: does one size fit all?
BJ Erickson, P Korfiatis, TL Kline, Z Akkus, K Philbrick, AD Weston
Journal of the American College of Radiology 15 (3), 521-526, 2018
1452018
RIL-Contour: a Medical Imaging Dataset Annotation Tool for and with Deep Learning
KA Philbrick, AD Weston, Z Akkus, TL Kline, P Korfiatis, T Sakinis, ...
Journal of digital imaging 32, 571-581, 2019
1252019
Monoallelic IFT140 pathogenic variants are an important cause of the autosomal dominant polycystic kidney-spectrum phenotype
SR Senum, YSM Li, KA Benson, G Joli, E Olinger, S Lavu, CD Madsen, ...
The American Journal of Human Genetics 109 (1), 136-156, 2022
1112022
Biocompatible high-moment FeCo-Au magnetic nanoparticles for magnetic hyperthermia treatment optimization
TL Kline, YH Xu, Y Jing, JP Wang
Journal of Magnetism and Magnetic Materials 321 (10), 1525-1528, 2009
1052009
Long-term administration of tolvaptan in autosomal dominant polycystic kidney disease
ME Edwards, FT Chebib, MV Irazabal, TG Ofstie, LA Bungum, AJ Metzger, ...
Clinical Journal of the American Society of Nephrology 13 (8), 1153-1161, 2018
992018
Automatic measurement of kidney and liver volumes from MR images of patients affected by autosomal dominant polycystic kidney disease
MDA van Gastel, ME Edwards, VE Torres, BJ Erickson, RT Gansevoort, ...
Journal of the American Society of Nephrology 30 (8), 1514-1522, 2019
902019
Randomised controlled trial to determine the efficacy and safety of prescribed water intake to prevent kidney failure due to autosomal dominant polycystic kidney disease …
ATY Wong, C Mannix, JJ Grantham, M Allman-Farinelli, SV Badve, ...
BMJ open 8 (1), e018794, 2018
872018
Noninvasive assessment of renal fibrosis with magnetization transfer MR imaging: validation and evaluation in murine renal artery stenosis
K Jiang, CM Ferguson, B Ebrahimi, H Tang, TL Kline, TA Burningham, ...
Radiology 283 (1), 77-86, 2017
872017
Radiomics-based machine-learning models can detect pancreatic cancer on prediagnostic computed tomography scans at a substantial lead time before clinical diagnosis
S Mukherjee, A Patra, H Khasawneh, P Korfiatis, N Rajamohan, G Suman, ...
Gastroenterology 163 (5), 1435-1446. e3, 2022
862022
Image texture features predict renal function decline in patients with autosomal dominant polycystic kidney disease
TL Kline, P Korfiatis, ME Edwards, KT Bae, A Yu, AB Chapman, M Mrug, ...
Kidney international 92 (5), 1206-1216, 2017
752017
The value of genotypic and imaging information to predict functional and structural outcomes in ADPKD
S Lavu, LE Vaughan, SR Senum, TL Kline, AB Chapman, RD Perrone, ...
JCI insight 5 (15), 2020
712020
What does deep learning see? Insights from a classifier trained to predict contrast enhancement phase from CT images
KA Philbrick, K Yoshida, D Inoue, Z Akkus, TL Kline, AD Weston, ...
American Journal of Roentgenology 211 (6), 1184-1193, 2018
712018
Automated segmentation of hyperintense regions in FLAIR MRI using deep learning
P Korfiatis, TL Kline, BJ Erickson
Tomography 2 (4), 334, 2016
712016
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Articles 1–20