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Robert J. Gillies
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2020 – today
- 2022
- [j8]Qibing Jiang, Praneeth Sudalagunta, Maria C. Silva, Rafael R. Canevarolo
, Xiaohong Zhao, Khandakar Tanvir Ahmed, Raghunandan Reddy Alugubelli, Gabriel Deavila, Alexandre Tungesvik, Lia Perez, Robert A. Gatenby, Robert J. Gillies, Rachid Baz, Mark B. Meads, Kenneth H. Shain, Ariosto Siqueira Silva, Wei Zhang
CancerCellTracker: a brightfield time-lapse microscopy framework for cancer drug sensitivity estimation. Bioinform. 38(16): 4002-4010 (2022) - 2021
- [c30]Rahul Paul, Sherzod Kariev, Dmitry Cherezov, Matthew B. Schabath, Robert J. Gillies
Deep radiomics: deep learning on radiomics texture images. Computer-Aided Diagnosis 2021 - 2020
- [j7]Rahul Paul
Convolutional Neural Network ensembles for accurate lung nodule malignancy prediction 2 years in the future. Comput. Biol. Medicine 122: 103882 (2020) - [j6]Pritam Mukherjee
A shallow convolutional neural network predicts prognosis of lung cancer patients in multi-institutional computed tomography image datasets. Nat. Mach. Intell. 2(5): 274-282 (2020) - [c29]Rahul Paul
Mitigating Adversarial Attacks on Medical Image Understanding Systems. ISBI 2020: 1517-1521
2010 – 2019
- 2019
- [c28]Rahul Paul
Towards deep radiomics: nodule malignancy prediction using CNNs on feature images. Computer-Aided Diagnosis 2019: 109503Z - 2018
- [j5]Saeed S. Alahmari
Delta Radiomics Improves Pulmonary Nodule Malignancy Prediction in Lung Cancer Screening. IEEE Access 6: 77796-77806 (2018) - [c27]Rahul Paul
Predicting Nodule Malignancy using a CNN Ensemble Approach. IJCNN 2018: 1-8 - [c26]Rahul Paul
Representation of Deep Features using Radiologist defined Semantic Features. IJCNN 2018: 1-7 - [c25]Wei Mu, Jin Qi, Hong Lu, Matthew B. Schabath, Yoganand Balagurunathan, Ilke Tunali, Robert James Gillies
Radiomic biomarkers from PET/CT multi-modality fusion images for the prediction of immunotherapy response in advanced non-small cell lung cancer patients. Computer-Aided Diagnosis 2018: 105753S - [c24]Rahul Paul
Stability of deep features across CT scanners and field of view using a physical phantom. Computer-Aided Diagnosis 2018: 105753P - 2017
- [c23]Sarfaraz Hussein, Robert J. Gillies
TumorNet: Lung nodule characterization using multi-view Convolutional Neural Network with Gaussian Process. ISBI 2017: 1007-1010 - [i1]Sarfaraz Hussein, Robert J. Gillies, Kunlin Cao, Qi Song, Ulas Bagci:
TumorNet: Lung Nodule Characterization Using Multi-View Convolutional Neural Network with Gaussian Process. CoRR abs/1703.00645 (2017) - 2016
- [j4]Jayashree Kalpathy-Cramer, Binsheng Zhao, Dmitry B. Goldgof, Yuhua Gu, Xingwei Wang, Hao Yang, Yongqiang Tan, Robert J. Gillies
A Comparison of Lung Nodule Segmentation Algorithms: Methods and Results from a Multi-institutional Study. J. Digit. Imaging 29(4): 476-487 (2016) - [c22]Baishali Chaudhury, Mu Zhou, Hamidreza Farhidzadeh, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies
Predicting Ki67% expression from DCE-MR images of breast tumors using textural kinetic features in tumor habitats. Computer-Aided Diagnosis 2016: 97850T - [c21]Hamidreza Farhidzadeh, Baishali Chaudhury, Jacob G. Scott, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies
Signal intensity analysis of ecological defined habitat in soft tissue sarcomas to predict metastasis development. Computer-Aided Diagnosis 2016: 97851H - [c20]Benjamin Geiger, Samuel H. Hawkins, Lawrence O. Hall, Dmitry B. Goldgof, Yoganand Balagurunathan, Robert A. Gatenby, Robert J. Gillies
Change descriptors for determining nodule malignancy in national lung screening trial CT screening images. Computer-Aided Diagnosis 2016: 978535 - [c19]Qian Li, Yoganand Balagurunathan, Ying Liu, Matthew B. Schabath
Performance comparison of quantitative semantic features and lung-RADS in the National Lung Screening Trial. Image Perception, Observer Performance, and Technology Assessment 2016: 97870H - [c18]Ying Liu, Yoganand Balagurunathan, Thomas Atwater, Sanja Antic, Qian Li, Ronald Walker, Gary T. Smith
Quantitative imaging features to predict cancer status in lung nodules. Image Perception, Observer Performance, and Technology Assessment 2016: 97870L - [c17]Dmitry Cherezov, Samuel H. Hawkins, Dmitry B. Goldgof, Lawrence O. Hall, Yoganand Balagurunathan, Robert J. Gillies, Matthew B. Schabath
Improving malignancy prediction through feature selection informed by nodule size ranges in NLST. SMC 2016: 1939-1944 - [c16]Rahul Paul
Combining deep neural network and traditional image features to improve survival prediction accuracy for lung cancer patients from diagnostic CT. SMC 2016: 2570-2575 - [c15]Hamidreza Farhidzadeh, Dmitry B. Goldgof, Lawrence O. Hall, Jacob G. Scott, Robert A. Gatenby, Robert J. Gillies, Meera Raghavan:
A quantitative histogram-based approach to predict treatment outcome for Soft Tissue Sarcomas using pre- and post-treatment MRIs. SMC 2016: 4549-4554 - 2015
- [c14]Hamidreza Farhidzadeh, Baishali Chaudhury, Mu Zhou, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies
Prediction of treatment outcome in soft tissue sarcoma based on radiologically defined habitats. Computer-Aided Diagnosis 2015: 94141U - [c13]Mu Zhou, Lawrence O. Hall, Dmitry B. Goldgof, Robert J. Gillies
Imbalanced learning for clinical survival group prediction of brain tumor patients. Computer-Aided Diagnosis 2015: 94142K - [c12]Mu Zhou, Lawrence O. Hall, Dmitry B. Goldgof, Robin Russo
Decoding brain cancer dynamics: a quantitative histogram-based approach using temporal MRI. Computer-Aided Diagnosis 2015: 94142H - [c11]Baishali Chaudhury, Mu Zhou, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies
Identifying metastatic breast tumors using textural kinetic features of a contrast based habitat in DCE-MRI. Computer-Aided Diagnosis 2015: 941415 - [c10]Baishali Chaudhury, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Jennifer S. Drukteinis:
Correlation Based Random Subspace Ensembles for Predicting Number of Axillary Lymph Node Metastases in Breast DCE-MRI Tumors. SMC 2015: 2164-2169 - [c9]Hailing Zhou
A Robust Approach for Automated Lung Segmentation in Thoracic CT. SMC 2015: 2267-2272 - [c8]Hamidreza Farhidzadeh, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Meera Raghavan:
Texture Feature Analysis to Predict Metastatic and Necrotic Soft Tissue Sarcomas. SMC 2015: 2798-2802 - 2014
- [j3]Samuel H. Hawkins, John N. Korecki
Predicting Outcomes of Nonsmall Cell Lung Cancer Using CT Image Features. IEEE Access 2: 1418-1426 (2014) - [j2]Yoganand Balagurunathan, Virendra Kumar
Test-Retest Reproducibility Analysis of Lung CT Image Features. J. Digit. Imaging 27(6): 805-823 (2014) - [c7]Baishali Chaudhury, Lawrence O. Hall, Dmitry B. Goldgof, Robert A. Gatenby, Robert J. Gillies, Jennifer S. Drukteinis:
New method for predicting estrogen receptor status utilizing breast MRI texture kinetic analysis. Computer-Aided Diagnosis 2014: 90351V - [c6]Baishali Chaudhury, Mu Zhou, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Jennifer S. Drukteinis:
Using features from tumor subregions of breast DCE-MRI for estrogen receptor status prediction. SMC 2014: 2624-2629 - 2013
- [j1]Yuhua Gu, Virendra Kumar
Automated delineation of lung tumors from CT images using a single click ensemble segmentation approach. Pattern Recognit. 46(3): 692-702 (2013) - [c5]Mu Zhou, Lawrence O. Hall, Dmitry B. Goldgof, Robert J. Gillies, Robert A. Gatenby:
Survival time prediction of patients with glioblastoma multiforme tumors using spatial distance measurement. Computer-Aided Diagnosis 2013: 86702O - [c4]Henry Krewer, Benjamin Geiger, Lawrence O. Hall, Dmitry B. Goldgof, Yuhua Gu, Melvyn Tockman, Robert J. Gillies:
Effect of Texture Features in Computer Aided Diagnosis of Pulmonary Nodules in Low-Dose Computed Tomography. SMC 2013: 3887-3891 - [c3]Mu Zhou, Lawrence O. Hall, Dmitry B. Goldgof, Robert A. Gatenby, Robert J. Gillies:
A Texture Feature Ranking Model for Predicting Survival Time of Brain Tumor Patients. SMC 2013: 4533-4538 - 2011
- [c2]Satrajit Basu, Lawrence O. Hall, Dmitry B. Goldgof, Yuhua Gu, Virendra Kumar
Developing a classifier model for lung tumors in CT-scan images. SMC 2011: 1306-1312
2000 – 2009
- 2008
- [c1]Rohit C. Philip, Jeffrey J. Rodriguez, Robert J. Gillies:
Seed pruning using a multi-resolution approach for automated segmentation of breast cancer tissue. ICIP 2008: 1436-1439
Coauthor Index
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