Saima Rathore
According to our database1,
Saima Rathore
authored at least 37 papers
between 2011 and 2023.
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Bibliography
2023
Imaging phenotypes predict overall survival in glioma more accurate than basic demographic and cell mutation profiles.
Comput. Methods Programs Biomed., December, 2023
2022
Deep radiomic signature with immune cell markers predicts the survival of glioma patients.
Neurocomputing, 2022
2020
Brain extraction on MRI scans in presence of diffuse glioma: Multi-institutional performance evaluation of deep learning methods and robust modality-agnostic training.
NeuroImage, 2020
Future Gener. Comput. Syst., 2020
IEEE Access, 2020
Integrative radiomic analysis for pre-surgical prognostic stratification of glioblastoma patients: from advanced to basic MRI protocols.
Proceedings of the Medical Imaging 2020: Image-Guided Procedures, 2020
2019
Multivariate Analysis of Preoperative Magnetic Resonance Imaging Reveals Transcriptomic Classification of de novo Glioblastoma Patients.
Frontiers Comput. Neurosci., 2019
Deep radiomic features from MRI scans predict survival outcome of recurrent glioblastoma.
CoRR, 2019
Prediction of overall survival and molecular markers in gliomas via analysis of digital pathology images using deep learning.
CoRR, 2019
Radiopathomics: Integration of radiographic and histologic characteristics for prognostication in glioblastoma.
CoRR, 2019
Applying Bayesian Network Approach to Determine the Association Between Morphological Features Extracted from Prostate Cancer Images.
IEEE Access, 2019
Imaging Signature of 1p/19q Co-deletion Status Derived via Machine Learning in Lower Grade Glioma.
Proceedings of the Radiomics and Radiogenomics in Neuro-oncology, 2019
Non-invasive transcriptomic classification of de novo Glioblastoma patients through multivariate quantitative analysis of baseline preoperative multimodal magnetic resonance imaging.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019
2018
A multi-modal, multi-atlas-based approach for Alzheimer detection via machine learning.
Int. J. Imaging Syst. Technol., 2018
Spatial Wavelet-Based Coherence and Coupling in EEG Signals With Eye Open and Closed During Resting State.
IEEE Access, 2018
Automated Breast Cancer Detection Using Machine Learning Techniques by Extracting Different Feature Extracting Strategies.
Proceedings of the 17th IEEE International Conference On Trust, 2018
Technical note: a radiomic signature of infiltration in peritumoral edema predicts subsequent recurrence in glioblastoma.
Proceedings of the Medical Imaging 2018: Image-Guided Procedures, 2018
Deriving stable multi-parametric MRI radiomic signatures in the presence of inter-scanner variations: survival prediction of glioblastoma via imaging pattern analysis and machine learning techniques.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
Proceedings of the 2018 International Conference on Frontiers of Information Technology, 2018
2017
A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages.
NeuroImage, 2017
Brain Cancer Imaging Phenomics Toolkit (brain-CaPTk): An Interactive Platform for Quantitative Analysis of Glioblastoma.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2017
2016
Frontiers Comput. Sci., 2016
Segmentation of Gliomas in Pre-operative and Post-operative Multimodal Magnetic Resonance Imaging Volumes Based on a Hybrid Generative-Discriminative Framework.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2016
Proceedings of the International Conference on Frontiers of Information Technology, 2016
2015
Comput. Methods Programs Biomed., 2015
Automated colon cancer detection using hybrid of novel geometric features and some traditional features.
Comput. Biol. Medicine, 2015
GLISTRboost: Combining Multimodal MRI Segmentation, Registration, and Biophysical Tumor Growth Modeling with Gradient Boosting Machines for Glioma Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2015
2014
IEEE ACM Trans. Comput. Biol. Bioinform., 2014
Robust brain MRI denoising and segmentation using enhanced non-local means algorithm.
Int. J. Imaging Syst. Technol., 2014
Int. J. Imaging Syst. Technol., 2014
Ensemble classification of colon biopsy images based on information rich hybrid features.
Comput. Biol. Medicine, 2014
2013
IEEE ACM Trans. Comput. Biol. Bioinform., 2013
Int. J. Imaging Syst. Technol., 2013
Proceedings of the 11th International Conference on Frontiers of Information Technology, 2013
2011
Proceedings of the 2011 Frontiers of Information Technology, 2011