Rathore, Saima
University of Pennsylvania
8 papers on CoChatORCID 0000-0003-4752-2298
Most cited papers
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A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages
Rathore, S., Habes, M., Iftikhar, M. A., Shacklett, A., & Davatzikos, C. (2017) · NeuroImage
Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatments
Cited by 622
- Verified
Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome
Davatzikos, C., Rathore, S., Bakas, S., Pati, S., Bergman, M., Kalarot, R., Sridharan, P., Gastounioti, A., Jahani, N., Cohen, E., et al. (2018) · Journal of Medical Imaging
Radiomics and Machine Learning in Medical ImagingMRI in cancer diagnosis
Cited by 204
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GLISTRboost: Combining Multimodal MRI Segmentation, Registration, and Biophysical Tumor Growth Modeling with Gradient Boosting Machines for Glioma Segmentation
Bakas, S., Zeng, K., Sotiras, A., Rathore, S., Akbari, H., Gaonkar, B., Rozycki, M., Pati, S., & Davatzikos, C. (2016) · Lecture Notes in Computer Science
Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques
Cited by 101
- Verified
The Cancer Imaging Phenomics Toolkit (CaPTk): Technical Overview
Pati, S., Singh, A., Rathore, S., Gastounioti, A., Bergman, M., Ngo, P., Ha, S. M., Bounias, D., Minock, J., Murphy, G., et al. (2020) · Lecture Notes in Computer Science
Radiomics and Machine Learning in Medical ImagingMedical Image Segmentation Techniques
Cited by 94
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Brain extraction on MRI scans in presence of diffuse glioma: Multi-institutional performance evaluation of deep learning methods and robust modality-agnostic training
Thakur, S., Doshi, J., Pati, S., Rathore, S., Sako, C., Bilello, M., Ha, S. M., Shukla, G., Flanders, A., Kotrotsou, A., et al. (2020) · NeuroImage
Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques
Cited by 84
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A multi-modal, multi-atlas-based approach for Alzheimer detection via machine learning
Asim, Y., Raza, B., Malik, A. K., Rathore, S., Hussain, L., & Iftikhar, M. A. (2018) · International Journal of Imaging Systems and Technology
Dementia and Cognitive Impairment ResearchFunctional Brain Connectivity Studies
Cited by 74
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Brain Cancer Imaging Phenomics Toolkit (brain-CaPTk): An Interactive Platform for Quantitative Analysis of Glioblastoma
Rathore, S., Bakas, S., Pati, S., Akbari, H., Kalarot, R., Sridharan, P., Rozycki, M., Bergman, M., Tunc, B., Verma, R., et al. (2018) · Lecture Notes in Computer Science
Radiomics and Machine Learning in Medical ImagingBrain Tumor Detection and Classification
Cited by 57
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Cancer Imaging Phenomics via CaPTk: Multi-Institutional Prediction of Progression-Free Survival and Pattern of Recurrence in Glioblastoma
Fathi Kazerooni, A., Akbari, H., Shukla, G., Badve, C., Rudie, J. D., Sako, C., Rathore, S., Bakas, S., Pati, S., Singh, A., et al. (2020) · JCO Clinical Cancer Informatics
Radiomics and Machine Learning in Medical ImagingGlioma Diagnosis and Treatment
Cited by 39
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