Robert J. Gillies
Orcid: 0000-0002-8888-7747
According to our database1,
Robert J. Gillies
authored at least 38 papers
between 2008 and 2022.
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Bibliography
2022
CancerCellTracker: a brightfield time-lapse microscopy framework for cancer drug sensitivity estimation.
Bioinform., 2022
2021
Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021
2020
A shallow convolutional neural network predicts prognosis of lung cancer patients in multi-institutional computed tomography image datasets.
Nat. Mach. Intell., 2020
Convolutional Neural Network ensembles for accurate lung nodule malignancy prediction 2 years in the future.
Comput. Biol. Medicine, 2020
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020
2019
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019
2018
Delta Radiomics Improves Pulmonary Nodule Malignancy Prediction in Lung Cancer Screening.
IEEE Access, 2018
Stability of deep features across CT scanners and field of view using a physical phantom.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
Radiomic biomarkers from PET/CT multi-modality fusion images for the prediction of immunotherapy response in advanced non-small cell lung cancer patients.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018
2017
TumorNet: Lung nodule characterization using multi-view Convolutional Neural Network with Gaussian Process.
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017
2016
A Comparison of Lung Nodule Segmentation Algorithms: Methods and Results from a Multi-institutional Study.
J. Digit. Imaging, 2016
Combining deep neural network and traditional image features to improve survival prediction accuracy for lung cancer patients from diagnostic CT.
Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics, 2016
A quantitative histogram-based approach to predict treatment outcome for Soft Tissue Sarcomas using pre- and post-treatment MRIs.
Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics, 2016
Improving malignancy prediction through feature selection informed by nodule size ranges in NLST.
Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics, 2016
Proceedings of the Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment, San Diego, California, United States, 27 February, 2016
Performance comparison of quantitative semantic features and lung-RADS in the National Lung Screening Trial.
Proceedings of the Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment, San Diego, California, United States, 27 February, 2016
Change descriptors for determining nodule malignancy in national lung screening trial CT screening images.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 2016
Signal intensity analysis of ecological defined habitat in soft tissue sarcomas to predict metastasis development.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 2016
Predicting Ki67% expression from DCE-MR images of breast tumors using textural kinetic features in tumor habitats.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 2016
2015
Proceedings of the 2015 IEEE International Conference on Systems, 2015
Proceedings of the 2015 IEEE International Conference on Systems, 2015
Correlation Based Random Subspace Ensembles for Predicting Number of Axillary Lymph Node Metastases in Breast DCE-MRI Tumors.
Proceedings of the 2015 IEEE International Conference on Systems, 2015
Decoding brain cancer dynamics: a quantitative histogram-based approach using temporal MRI.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015
Prediction of treatment outcome in soft tissue sarcoma based on radiologically defined habitats.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015
Identifying metastatic breast tumors using textural kinetic features of a contrast based habitat in DCE-MRI.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015
2014
J. Digit. Imaging, 2014
IEEE Access, 2014
Using features from tumor subregions of breast DCE-MRI for estrogen receptor status prediction.
Proceedings of the 2014 IEEE International Conference on Systems, Man, and Cybernetics, 2014
New method for predicting estrogen receptor status utilizing breast MRI texture kinetic analysis.
Proceedings of the Medical Imaging 2014: Computer-Aided Diagnosis, 2014
2013
Automated delineation of lung tumors from CT images using a single click ensemble segmentation approach.
Pattern Recognit., 2013
A Texture Feature Ranking Model for Predicting Survival Time of Brain Tumor Patients.
Proceedings of the IEEE International Conference on Systems, 2013
Effect of Texture Features in Computer Aided Diagnosis of Pulmonary Nodules in Low-Dose Computed Tomography.
Proceedings of the IEEE International Conference on Systems, 2013
Survival time prediction of patients with glioblastoma multiforme tumors using spatial distance measurement.
Proceedings of the Medical Imaging 2013: Computer-Aided Diagnosis, 2013
2011
Proceedings of the IEEE International Conference on Systems, 2011
2008
Seed pruning using a multi-resolution approach for automated segmentation of breast cancer tissue.
Proceedings of the International Conference on Image Processing, 2008