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), 1-8, 2017
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), 1-14, 2015
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
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), 1-11, 2018
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), 1-7, 2017
Prostate Cancer Detection using Deep Convolutional Neural Networks
S Yoo, I Gujrathi, MA Haider, F Khalvati
Scientific Reports 9, 2019
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
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), 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, 2017
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), 1-9, 2019
Autoencoding the retrieval relevance of medical images
Z Camlica, HR Tizhoosh, F Khalvati
2015 International Conference on Image Processing Theory, Tools and …, 2015
Automated Segmentation of Breast in 3D MR Images Using a Robust Atlas
F Khalvati, C Gallego Ortiz, S Balasingham, A Martel
IEEE Transactions on Medical Imaging, 2015
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), 1-8, 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
Fully Deep Convolutional Neural Networks for Segmentation of the Prostate Gland in Diffusion-Weighted MR Images
T Clark, A Wong, MA Haider, F Khalvati
International Conference on Image Analysis and Recognition (ICIAR) 10317, 97-104, 2017
Prostate Cancer Detection via a Quantitative Radiomics-Driven Conditional Random Field Framework
A Chung, F Khalvati, M Shafiee, M Haider, A Wong
IEEE Access 3, 2531 - 2541, 2015
MPCaD: a multi-scale radiomics-driven framework for automated prostate cancer localization and detection
F Khalvati, J Zhang, AG Chung, MJ Shafiee, A Wong, MA Haider
BMC medical imaging 18 (1), 1-14, 2018
RANDGAN: randomized generative adversarial network for detection of COVID-19 in chest X-ray
S Motamed, P Rogalla, F Khalvati
Scientific Reports 11 (1), 1-10, 2021
EFIS–Evolving Fuzzy Image Segmentation
A Othman, H Tizhoosh, F Khalvati
IEEE Transactions on Fuzzy Systems 22 (1), 72-82, 2014
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