Seed pruning using a multi-resolution approach for automated segmentation of breast cancer tissue. - Rohit C. Philip; Jeffrey J. Rodriguez; Robert J. Gillies (ICIP, 2008)

Developing a classifier model for lung tumors in CT-scan images. - Satrajit Basu; Lawrence O. Hall; Dmitry B. Goldgof; Yuhua Gu; Virendra Kumar; Jung Choi; Robert J. Gillies; Robert A. Gatenby (SMC, 2011)

Survival time prediction of patients with glioblastoma multiforme tumors using spatial distance measurement. - Mu Zhou; Lawrence O. Hall; Dmitry B. Goldgof; Robert J. Gillies; Robert A. Gatenby (Computer-Aided Diagnosis, 2013)

Effect of Texture Features in Computer Aided Diagnosis of Pulmonary Nodules in Low-Dose Computed Tomography. - Henry Krewer; Benjamin Geiger; Lawrence O. Hall; Dmitry B. Goldgof; Yuhua Gu; Melvyn Tockman; Robert J. Gillies (SMC, 2013)

A Texture Feature Ranking Model for Predicting Survival Time of Brain Tumor Patients. - Mu Zhou; Lawrence O. Hall; Dmitry B. Goldgof; Robert A. Gatenby; Robert J. Gillies (SMC, 2013)

Automated delineation of lung tumors from CT images using a single click ensemble segmentation approach. - Yuhua Gu; Virendra Kumar; Lawrence O. Hall; Dmitry B. Goldgof; Ching-Yen Li; René Korn; Claus Bendtsen; Emmanuel Rios Velazquez; Andre Dekker; Hugo J. W. L. Aerts; Philippe Lambin; Xiuli Li; et al. (Pattern Recognit., 2013)

New method for predicting estrogen receptor status utilizing breast MRI texture kinetic analysis. - Baishali Chaudhury; Lawrence O. Hall; Dmitry B. Goldgof; Robert A. Gatenby; Robert J. Gillies; Jennifer S. Drukteinis (Computer-Aided Diagnosis, 2014)

Using features from tumor subregions of breast DCE-MRI for estrogen receptor status prediction. - Baishali Chaudhury; Mu Zhou; Dmitry B. Goldgof; Lawrence O. Hall; Robert A. Gatenby; Robert J. Gillies; Jennifer S. Drukteinis (SMC, 2014)

Predicting Outcomes of Nonsmall Cell Lung Cancer Using CT Image Features. - Samuel H. Hawkins; John N. Korecki; Yoganand Balagurunathan; Yuhua Gu; Virendra Kumar; Satrajit Basu; Lawrence O. Hall; Dmitry B. Goldgof; Robert A. Gatenby; Robert J. Gillies (IEEE Access, 2014)

Test-Retest Reproducibility Analysis of Lung CT Image Features. - Yoganand Balagurunathan; Virendra Kumar; Yuhua Gu; Jongphil Kim; Hua Wang; Ying Liu; Dmitry B. Goldgof; Lawrence O. Hall; René Korn; Binsheng Zhao; Lawrence H. Schwartz; Satrajit Basu; et al. (J. Digit. Imaging, 2014)

Identifying metastatic breast tumors using textural kinetic features of a contrast based habitat in DCE-MRI. - Baishali Chaudhury; Mu Zhou; Dmitry B. Goldgof; Lawrence O. Hall; Robert A. Gatenby; Robert J. Gillies; Jennifer S. Drukteinis (Computer-Aided Diagnosis, 2015)

Prediction of treatment outcome in soft tissue sarcoma based on radiologically defined habitats. - Hamidreza Farhidzadeh; Baishali Chaudhury; Mu Zhou; Dmitry B. Goldgof; Lawrence O. Hall; Robert A. Gatenby; Robert J. Gillies; Meera Raghavan (Computer-Aided Diagnosis, 2015)

Imbalanced learning for clinical survival group prediction of brain tumor patients. - Mu Zhou; Lawrence O. Hall; Dmitry B. Goldgof; Robert J. Gillies; Robert A. Gatenby (Computer-Aided Diagnosis, 2015)

Decoding brain cancer dynamics: a quantitative histogram-based approach using temporal MRI. - Mu Zhou; Lawrence O. Hall; Dmitry B. Goldgof; Robin Russo; Robert J. Gillies; Robert A. Gatenby (Computer-Aided Diagnosis, 2015)

Correlation Based Random Subspace Ensembles for Predicting Number of Axillary Lymph Node Metastases in Breast DCE-MRI Tumors. - Baishali Chaudhury; Dmitry B. Goldgof; Lawrence O. Hall; Robert A. Gatenby; Robert J. Gillies; Jennifer S. Drukteinis (SMC, 2015)

Texture Feature Analysis to Predict Metastatic and Necrotic Soft Tissue Sarcomas. - Hamidreza Farhidzadeh; Dmitry B. Goldgof; Lawrence O. Hall; Robert A. Gatenby; Robert J. Gillies; Meera Raghavan (SMC, 2015)

A Robust Approach for Automated Lung Segmentation in Thoracic CT. - Hailing Zhou; Dmitry B. Goldgof; Samuel H. Hawkins; Lei Wei 002; Ying Liu; Douglas C. Creighton; Robert J. Gillies; Lawrence O. Hall; Saeid Nahavandi (SMC, 2015)

Predicting Ki67% expression from DCE-MR images of breast tumors using textural kinetic features in tumor habitats. - Baishali Chaudhury; Mu Zhou; Hamidreza Farhidzadeh; Dmitry B. Goldgof; Lawrence O. Hall; Robert A. Gatenby; Robert J. Gillies; Robert J. Weinfurtner; Jennifer S. Drukteinis (Computer-Aided Diagnosis, 2016)

Signal intensity analysis of ecological defined habitat in soft tissue sarcomas to predict metastasis development. - Hamidreza Farhidzadeh; Baishali Chaudhury; Jacob G. Scott; Dmitry B. Goldgof; Lawrence O. Hall; Robert A. Gatenby; Robert J. Gillies; Meera Raghavan (Computer-Aided Diagnosis, 2016)

Change descriptors for determining nodule malignancy in national lung screening trial CT screening images. - Benjamin Geiger; Samuel H. Hawkins; Lawrence O. Hall; Dmitry B. Goldgof; Yoganand Balagurunathan; Robert A. Gatenby; Robert J. Gillies (Computer-Aided Diagnosis, 2016)

Performance comparison of quantitative semantic features and lung-RADS in the National Lung Screening Trial. - Qian Li; Yoganand Balagurunathan; Ying Liu; Matthew B. Schabath; Robert J. Gillies (Image Perception, Observer Performance, and Technology Assessment, 2016)

Quantitative imaging features to predict cancer status in lung nodules. - Ying Liu; Yoganand Balagurunathan; Thomas Atwater; Sanja Antic; Qian Li; Ronald Walker; Gary T. Smith; Pierre P. Massion; Matthew B. Schabath; Robert J. Gillies (Image Perception, Observer Performance, and Technology Assessment, 2016)

Improving malignancy prediction through feature selection informed by nodule size ranges in NLST. - Dmitry Cherezov; Samuel H. Hawkins; Dmitry B. Goldgof; Lawrence O. Hall; Yoganand Balagurunathan; Robert J. Gillies; Matthew B. Schabath (SMC, 2016)

A quantitative histogram-based approach to predict treatment outcome for Soft Tissue Sarcomas using pre- and post-treatment MRIs. - Hamidreza Farhidzadeh; Dmitry B. Goldgof; Lawrence O. Hall; Jacob G. Scott; Robert A. Gatenby; Robert J. Gillies; Meera Raghavan (SMC, 2016)

Combining deep neural network and traditional image features to improve survival prediction accuracy for lung cancer patients from diagnostic CT. - Rahul Paul; Samuel H. Hawkins; Lawrence O. Hall; Dmitry B. Goldgof; Robert J. Gillies (SMC, 2016)

A Comparison of Lung Nodule Segmentation Algorithms: Methods and Results from a Multi-institutional Study. - Jayashree Kalpathy-Cramer; Binsheng Zhao; Dmitry B. Goldgof; Yuhua Gu; Xingwei Wang 004; Hao Yang; Yongqiang Tan; Robert J. Gillies; Sandy Napel (J. Digit. Imaging, 2016)

TumorNet: Lung nodule characterization using multi-view Convolutional Neural Network with Gaussian Process. - Sarfaraz Hussein; Robert J. Gillies; Kunlin Cao; Qi Song 001; Ulas Bagci (ISBI, 2017)

Predicting Nodule Malignancy using a CNN Ensemble Approach. - Rahul Paul; Lawrence O. Hall; Dmitry B. Goldgof; Matthew B. Schabath; Robert J. Gillies (IJCNN, 2018)

Representation of Deep Features using Radiologist defined Semantic Features. - Rahul Paul; Ying Liu; Qian Li; Lawrence O. Hall; Dmitry B. Goldgof; Yoganand Balagurunathan; Matthew B. Schabath; Robert J. Gillies (IJCNN, 2018)

Radiomic biomarkers from PET/CT multi-modality fusion images for the prediction of immunotherapy response in advanced non-small cell lung cancer patients. - Wei Mu; Jin Qi; Hong Lu; Matthew B. Schabath; Yoganand Balagurunathan; Ilke Tunali; Robert James Gillies (Computer-Aided Diagnosis, 2018)

Stability of deep features across CT scanners and field of view using a physical phantom. - Rahul Paul; Muhammad Shafiq-ul-Hassan; Eduardo G. Moros; Robert J. Gillies; Lawrence O. Hall; Dmitry B. Goldgof (Computer-Aided Diagnosis, 2018)

Delta Radiomics Improves Pulmonary Nodule Malignancy Prediction in Lung Cancer Screening. - Saeed S. Alahmari; Dmitry Cherezov; Dmitry B. Goldgof; Lawrence O. Hall; Robert J. Gillies; Matthew B. Schabath (IEEE Access, 2018)

Towards deep radiomics: nodule malignancy prediction using CNNs on feature images. - Rahul Paul; Dmitry Cherezov; Matthew B. Schabath; Robert J. Gillies; Lawrence O. Hall; Dmitry B. Goldgof (Computer-Aided Diagnosis, 2019)

Mitigating Adversarial Attacks on Medical Image Understanding Systems. - Rahul Paul; Matthew B. Schabath; Robert J. Gillies; Lawrence O. Hall; Dmitry B. Goldgof (ISBI, 2020)

Convolutional Neural Network ensembles for accurate lung nodule malignancy prediction 2 years in the future. - Rahul Paul; Matthew B. Schabath; Robert J. Gillies; Lawrence O. Hall; Dmitry B. Goldgof (Comput. Biol. Medicine, 2020)

A shallow convolutional neural network predicts prognosis of lung cancer patients in multi-institutional computed tomography image datasets. - Pritam Mukherjee; Mu Zhou; Edward Lee; Anne Schicht; Yoganand Balagurunathan; Sandy Napel; Robert J. Gillies; Simon Wong; Alexander Thieme; Ann N. Leung; Olivier Gevaert (Nat. Mach. Intell., 2020)

Deep radiomics: deep learning on radiomics texture images. - Rahul Paul; Sherzod Kariev; Dmitry Cherezov; Matthew B. Schabath; Robert J. Gillies; Lawrence O. Hall; Dmitry B. Goldgof (Computer-Aided Diagnosis, 2021)

CancerCellTracker: a brightfield time-lapse microscopy framework for cancer drug sensitivity estimation. - 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; et al. (Bioinform., 2022)