Dmitry Cherezov
Cited by
Cited by
Predicting malignant nodules from screening CT scans
S Hawkins, H Wang, Y Liu, A Garcia, O Stringfield, H Krewer, Q Li, ...
Journal of Thoracic Oncology 11 (12), 2120-2128, 2016
Radiomics of lung nodules: a multi-institutional study of robustness and agreement of quantitative imaging features
J Kalpathy-Cramer, A Mamomov, B Zhao, L Lu, D Cherezov, S Napel, ...
Tomography 2 (4), 430-437, 2016
Delta radiomics improves pulmonary nodule malignancy prediction in lung cancer screening
SS Alahmari, D Cherezov, DB Goldgof, LO Hall, RJ Gillies, MB Schabath
Ieee Access 6, 77796-77806, 2018
Stability and reproducibility of computed tomography radiomic features extracted from peritumoral regions of lung cancer lesions
I Tunali, LO Hall, S Napel, D Cherezov, A Guvenis, RJ Gillies, ...
Medical physics 46 (11), 5075-5085, 2019
Revealing tumor habitats from texture heterogeneity analysis for classification of lung cancer malignancy and aggressiveness
D Cherezov, D Goldgof, L Hall, R Gillies, M Schabath, H Müller, ...
Scientific reports 9 (1), 4500, 2019
Delta radiomic features improve prediction for lung cancer incidence: A nested case–control analysis of the National Lung Screening Trial
D Cherezov, SH Hawkins, DB Goldgof, LO Hall, Y Liu, Q Li, ...
Cancer medicine 7 (12), 6340-6356, 2018
A radiogenomics ensemble to predict EGFR and KRAS mutations in NSCLC
S Moreno, M Bonfante, E Zurek, D Cherezov, D Goldgof, L Hall, ...
Tomography 7 (2), 154-168, 2021
Semi‐automated pulmonary nodule interval segmentation using the NLST data
Y Balagurunathan, A Beers, J Kalpathy‐Cramer, M McNitt‐Gray, ...
Medical physics 45 (3), 1093-1107, 2018
Lung nodule sizes are encoded when scaling CT image for CNN's
D Cherezov, R Paul, N Fetisov, RJ Gillies, MB Schabath, DB Goldgof, ...
Tomography 6 (2), 209-215, 2020
Improving malignancy prediction through feature selection informed by nodule size ranges in NLST
D Cherezov, S Hawkins, D Goldgof, L Hall, Y Balagurunathan, RJ Gillies, ...
2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2016
Deep radiomics: deep learning on radiomics texture images
R Paul, S Kariev, D Cherezov, MB Schabath, RJ Gillies, LO Hall, ...
Medical Imaging 2021: Computer-Aided Diagnosis 11597, 8-17, 2021
Towards deep radiomics: nodule malignancy prediction using CNNs on feature images
R Paul, D Cherezov, MB Schabath, RJ Gillies, LO Hall, DB Goldgof
Medical Imaging 2019: Computer-Aided Diagnosis 10950, 997-1003, 2019
Resolving impact of technical and biological variability on the convolutional neural networks: evaluating chest x-ray scans
D Cherezov, VS Viswanathan, A Gupta, A Madabhushi
Medical Imaging 2023: Image Processing 12464, 792-803, 2023
Rank acquisition impact on radiomics estimation (AсquIRE) in chest CT imaging: A retrospective multi-site, multi-use-case study
D Cherezov, VS Viswanathan, P Fu, A Gupta, A Madabhushi
Computer methods and programs in biomedicine 244, 107990, 2024
A Radiogenomics Ensemble to Predict EGFR and KRAS Mutations in NSCLC. Tomography 2021, 7, 154–168
S Moreno, M Bonfante, E Zurek, D Cherezov, D Goldgof, L Hall, ...
s Note: MDPI stays neutral with regard to jurisdictional claims in published …, 2021
Standardization in Quantitative Imaging: A Comparison of Radiomics Feature Values Obtained by Different Software Packages On a Set of Digital Reference Objects
M McNitt-Gray, S Napel, J Kalpathy-Cramer, A Jaggi, D Cherezov, ...
MEDICAL PHYSICS 46 (6), E400-E400, 2019
P1. 03-063 Quantitative Imaging Features Predict Incidence Lung Cancer in Low-Dose Computed Tomography (LDCT) Screening: Topic: Screening
D Cherezov, S Hawkins, D Goldgof, L Hall, Y Balagurunathan, R Gillies, ...
Journal of Thoracic Oncology 12 (1), S582, 2017
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