Farzad Khalvati
Farzad Khalvati
AI Chair in Medical Imaging, The Hospital for Sick Children, University of Toronto
Verified email at - Homepage
Cited by
Cited by
Radiomics-based prognosis analysis for non-small cell lung cancer
Y Zhang, A Oikonomou, A Wong, MA Haider, F Khalvati
Scientific reports 7 (1), 46349, 2017
MAPS: a quantitative radiomics approach for prostate cancer detection
A Cameron, F Khalvati, MA Haider, A Wong
IEEE Transactions on Biomedical Engineering 63 (6), 1145-1156, 2015
Automated prostate cancer detection via comprehensive multi-parametric magnetic resonance imaging texture feature models
F Khalvati, A Wong, MA Haider
BMC medical imaging 15, 1-14, 2015
Prostate Cancer Detection using Deep Convolutional Neural Networks
S Yoo, I Gujrathi, MA Haider, F Khalvati
Scientific Reports 9, 2019
Radiomics analysis at PET/CT contributes to prognosis of recurrence and survival in lung cancer treated with stereotactic body radiotherapy
A Oikonomou, F Khalvati, PN Tyrrell, MA Haider, U Tarique, ...
Scientific reports 8 (1), 4003, 2018
Data augmentation using Generative Adversarial Networks (GANs) for GAN-based detection of Pneumonia and COVID-19 in chest X-ray images
S Motamed, P Rogalla, F Khalvati
Informatics in medicine unlocked 27, 100779, 2021
CT texture features are associated with overall survival in pancreatic ductal adenocarcinoma a quantitative analysis
A Eilaghi, S Baig, Y Zhang, J Zhang, P Karanicolas, S Gallinger, ...
BMC medical imaging 17, 1-7, 2017
Medical image classification via SVM using LBP features from saliency-based folded data
Z Camlica, HR Tizhoosh, F Khalvati
2015 IEEE 14th international conference on machine learning and applications …, 2015
Radiomics, machine learning, and artificial intelligence—what the neuroradiologist needs to know
MW Wagner, K Namdar, A Biswas, S Monah, F Khalvati, BB Ertl-Wagner
Neuroradiology, 1-11, 2021
Can machine learning radiomics provide pre-operative differentiation of combined hepatocellular cholangiocarcinoma from hepatocellular carcinoma and cholangiocarcinoma to …
X Liu, F Khalvati, K Namdar, S Fischer, S Lewis, B Taouli, MA Haider, ...
European Radiology 31, 244-255, 2021
Discovery Radiomics for Pathologically-Proven Computed Tomography Lung Cancer Prediction
D Kumar, AG Chung, MJ Shaifee, F Khalvati, MA Haider, A Wong
Image Analysis and Recognition: 14th International Conference, ICIAR 2017 …, 2017
CT texture analysis: a potential tool for prediction of survival in patients with metastatic clear cell carcinoma treated with sunitinib
MA Haider, A Vosough, F Khalvati, A Kiss, B Ganeshan, GA Bjarnason
Cancer Imaging 17, 1-9, 2017
Fully automated segmentation of prostate whole gland and transition zone in diffusion-weighted MRI using convolutional neural networks
T Clark, J Zhang, S Baig, A Wong, MA Haider, F Khalvati
Journal of Medical Imaging 4 (4), 041307-041307, 2017
CNN-based survival model for pancreatic ductal adenocarcinoma in medical imaging
Y Zhang, EM Lobo-Mueller, P Karanicolas, S Gallinger, MA Haider, ...
BMC medical imaging 20, 1-8, 2020
Prognostic value of CT radiomic features in resectable pancreatic ductal adenocarcinoma
F Khalvati, Y Zhang, S Baig, EM Lobo-Mueller, P Karanicolas, S Gallinger, ...
Scientific reports 9 (1), 5449, 2019
RANDGAN: randomized generative adversarial network for detection of COVID-19 in chest X-ray
S Motamed, P Rogalla, F Khalvati
Scientific Reports 11 (1), 8602, 2021
A brief review of deep multi-task learning and auxiliary task learning
P Vafaeikia, K Namdar, F Khalvati
arXiv preprint arXiv:2007.01126, 2020
Value of increasing biopsy cores per target with cognitive MRI-targeted transrectal US prostate biopsy
M Zhang, L Milot, F Khalvati, L Sugar, M Downes, SM Baig, L Klotz, ...
Radiology 291 (1), 83-89, 2019
A comprehensive study of data augmentation strategies for prostate cancer detection in diffusion-weighted MRI using convolutional neural networks
R Hao, K Namdar, L Liu, MA Haider, F Khalvati
Journal of Digital Imaging 34, 862-876, 2021
A transfer learning–based active learning framework for brain tumor classification
R Hao, K Namdar, L Liu, F Khalvati
Frontiers in artificial intelligence 4, 635766, 2021
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