Publications

2020

  1. S. Akbarian, L. Seyyed-Kalantari, F. Khalvati, E. Dolatabadi. “Evaluating Knowledge Transfer in Neural Network for Medical Images.” arXiv, 2020. Online Link
  2. P. Vafaeikia, K. Namdar, F. Khalvati. “A Brief Review of Deep Multi-task Learning and Auxiliary Task Learning.” arXiv, 2020. Online Link
  3. S. Motamed, F. Khalvati. “Inception-Augmentation Generative Adversarial Network.” arXiv, 2020. Online Link 
  4. K. Namdar, M. A. Haider, F. Khalvati. “A Modified AUC for Training Convolutional Neural Networks: Taking Confidence into Account.” arXiv, 2020. Online Link
  5. R. Hao, K. Namdar, I. Gujrathi, L. Liu, M. A. Haider, F. Khalvati. “A Comprehensive Study of Data Augmentation Strategies for Prostate Cancer Detection in Diffusion Weighted MRI using Convolutional Neural Networks.” arXiv, 2020. Online Link
  6. Y. Zhang, E. M. Lobo-Mueller, P. Karanicolas, S. Gallinger, M. A. Haider, F. Khalvati. “Prognostic Value of Transfer Learning Based Features in Resectable Pancreatic Ductal Adenocarcinoma.” Frontiers in Artificial Intelligence – Medicine and Public Health, 2020. Online Link
  7. Y. Zhang, E. M. Lobo-Mueller, P. Karanicolas, S. Gallinger, M. A. Haider, F. Khalvati. “CNN-based Survival Model for Pancreatic Ductal Adenocarcinoma in Medical Imaging.” BMC Medical Imaging, 20(11), 2020. Online Link
  8. D. Deniffel, N. Abraham, K. Namdar, X. Dong, E. Salinas, L. Milot, F. Khalvati, M. A. Haider. “Using Decision Curve Analysis to Benchmark Performance of a Magnetic Resonance Imaging–based Deep Learning Model for Prostate Cancer Risk Assessment.” European Radiology, 2020. Online Link
  9. X. Liu, F. Khalvati, K. Namdar, S. Fischer, S. Lewis, B. Taouli, M. A. Haider, K. S. Jhaveri. “Can Machine Learning Radiomics Provide Pre-Operative Differentiation of Combined Hepatocellular Cholangiocarcinoma from Hepatocellular Carcinoma and Cholangiocarcinoma to Inform Optimal Treatment Planning?” European Radiology, 2020. Online Link
  10. C. Dulhanty, L. Wang, M. Cheng, H. Gunraj, F. Khalvati, M. A. Haider, A. Wong. “Radiomics Driven Diffusion Weighted Imaging Sensing Strategies for Zone-level Prostate Cancer Sensing.” Sensors, 2020. Online Link
  11. D. Deniffel, Y. Zhang, E. Salinas, R. Satkunasivam, F. Khalvati, M. A. Haider. “Reducing Unnecessary Prostate Multiparametric Magnetic Resonance Imaging by Using Clinical Parameters to Predict Negative and Indeterminate Findings.” The Journal of Urology, Vol. 203, No. 2, 2020. Online Link  
  12. D. Deniffel, N. Abraham, K. Namdar, S. Motamed, I. Gujrathi, E. Salinas, F. Khalvati, M. A. Haider. “Individualized Prostate Cancer Risk Assessment using MRI-based Deep Learning Compared to Multivariate Risk Modeling Including PI-RADSv2: A Decision Curve Analysis.” Proceedings of European Congress of Radiology (ECR), Vienna, Austria, 2020. 
  13. D. Deniffel, K. Namdar, I. Gujrathi, E. Salinas, A. Toi, A. Finelli, F. Khalvati, M. A. Haider. “Safe Reduction of MRI-targeted Biopsies in Men with PI-RADSv2 Category 3 Lesions: Cross-institutional Validation of a Multivariate Risk Model Based on Clinical Parameters.” Proceedings of European Congress of Radiology (ECR), Vienna, Austria, 2020.
  14. E. Salinas, K. Namdar, F. Khalvati, D. Deniffel, P. Abreu, T. Ivanics, G. Sapisochin, M. A. Haider, P. Veit-Haibach. “Prediction of Tumor Progression and Recurrence in Patients with Hepatocellular Carcinoma Undergoing Trans-arterial Chemoembolization as a Bridge to Transplant Using CT Radiomics Features.” Proceedings of European Congress of Radiology (ECR), Vienna, Austria, 2020. 
  15. E. Salinas, F. Khalvati, D. G. O’kane, X. Dong, D. J. Knox, O. Bathe, V. Baracos, S. Gallinger, M. A. Haider. “The Rate of Muscle Loss Measured with CT is a Prognostic Marker in Patients with Unresectable Pancreatic Cancer Receiving FOLFIRINOX.” Proceedings of European Congress of Radiology (ECR), Vienna, Austria, 2020. 

2019

  1. S. Motamed, I. Gujrathi, D. Deniffel, A. Oentoro, M. A. Haider, F. Khalvati. “A Transfer Learning Approach for Automated Segmentation of Prostate Whole Gland and Transition Zone in Diffusion Weighted MRI.” arXiv, 2019. Online Link
  2. Y. Zhang, E. M. Lobo-Mueller, P. Karanicolas, S. Gallinger, M. A. Haider, F. Khalvati. “Improving Prognostic Performance in Resectable Pancreatic Ductal Adenocarcinoma using Radiomics and Deep Learning Features Fusion in CT Images.” arXiv, 2019. Online Link
  3. S. Yoo, I. Gujrathi, M. A. Haider, F. Khalvati. “Prostate Cancer Detection via Deep Convolutional Neural Networks.” Nature Scientific Reports, 9, 19518, 2019. Online Link
  4. F. Khalvati, Y. Zhang, S. Baig, E. M. Lobo Mueller, P. Karanicolas, S. Gallinger, M. A. Haider. “Prognostic Value of CT Radiomic Features in Pancreatic Ductal Adenocarcinoma.” Nature Scientific Reports, 9, 5449, 2019. Online Link
  5. M. Zhang, L. Milot, F. Khalvati, L. Sugar, M. Downes, S. Baig, L. Klotz, M. A. Haider. “Value of Increasing Biopsy Cores per Target with Cognitive MRI-targeted Transrectal US Prostate Biopsy.” Radiology, Vol. 291, No. 1, 2019. Online Link
  6. D. Marman, F. Khalvati, M. Shafaei. “The Hidden Teachings of Rumi.” 324 pages, Spiritual Dialogues Project, 2019. Online Link
  7. F. Khalvati, Y. Zhang, A. Wong, M. A. Haider. “Radiomics.” Encyclopedia of Biomedical Engineering, vol. 2, pp. 597-603. Elsevier, 2019. Online Link 
  8. K. Namdar, I. Gujrathi, M. A. Haider, F. Khalvati. “Evolution-based Fine-tuning of CNNs for Prostate Cancer Detection.” Proceedings of International Conference on Neural Information Systems (NeurIPS) Workshops, Vancouver, BC, Canada, 2019. Among Top 5 Submissions. Online Link
  9. L. Wang, C. Dulhanty, A. G. Cheng, F. Khalvati, M. A. Haider, A. Wong. “Zone-DR: Discovery Radiomics via Zone-level Deep Radiomic Sequencer Discovery for Zone-based Prostate Cancer Grading using Diffusion Weighted Imaging.” Proceedings of International Conference on Neural Information Systems (NeurIPS) Workshops, Vancouver, BC, Canada, 2019. 
  10. F. Khalvati, Y. Zhang, P. H. U. Le, I. Gujrathi, M. A. Haider. “PI-RADS Guided Discovery Radiomics for Characterization of Prostate Lesions with Diffusion-Weighted MRI.” Proceedings of SPIE Medical Imaging, San Diego, CA, USA, 2019. Online Link
  11. X. Liu, F. Khalvati, K. Namdar, S. Fischer, M. A. Haider, K. S. Jhaveri. “Application of Radiomic MRI Features in Differentiation of Combined Hepatocellular Cholangiocarcinoma, Cholangiocarcinoma, and Hepatocellular Carcinoma Using Machine Learning.” Proceedings of Annual Meeting and Exhibition of the Radiological Society of North America (RSNA), Chicago, IL, USA, 2019. 
  12. D. Deniffel, Y. Zhang, E. Salinas, R. Satkunasivam, F. Khalvati, M. A. Haider. “Towards Reducing Overutilization of Prostate mpMRI: Using PSA Density to Predict Negative and Indeterminate MRI Scans.” Proceedings of Annual Meeting and Exhibition of the Radiological Society of North America (RSNA), Chicago, IL, USA, 2019. 
  13. J. He, E. Tio, L. Wang, C. Dulhanty, F. Khalvati, M. A. Haider, A. Wong. “A Comparative Study Between Apparent Diffusion Imaging and Correlated Diffusion Imaging for Prostate Cancer.” Proceedings of Conference on Vision and Imaging Systems, Waterloo, ON, Canada, 2019. 
  14. L. Wang, C. Dulhanty, A. Chung, F. Khalvati, M. A. Haider, A. Wong. “Zone-DR: Discovery Radiomics via Zone-level Deep Radiomic Sequencer Discovery for Zone-based Prostate Cancer Grading using Diffusion Weighted Imaging.” Proceedings of Conference on Vision and Imaging Systems, Waterloo, ON, Canada, 2019. 

2018

  1. F. Khalvati, J. Zhang, A. G. Chung, M. J. Shafiee, A. Wong, M. A. Haider. “MPCaD: A Multi-Scale Radiomics-Driven Framework for Automated Prostate Cancer Localization and Detection.” BMC Medical Imaging, 18:16, 2018. Online Link
  2. A. Oikonomou, F. Khalvati, P. N. Tyrrell, M. A. Haider, U. Tarique, L. Jimenez-Juan, M. C. Tjong, I. Poon, A. Eilaghi, L. Ehrlich, P. Cheung. “Radiomics Analysis at PET/CT Contributes to Prognosis of Recurrence and Survival in Lung Cancer Treated with Stereotactic Body Radiotherapy.” Nature Scientific Reports, 8, 4003, 2018. Online Link
  3. X. Hu, A. G. Chung, P. Fieguth, F. Khalvati, M. A. Haider, A. Wong. “ProstateGAN: Mitigating Data Bias via Prostate Diffusion Imaging Synthesis with Generative Adversarial Networks.” Proceedings of International Conference on Neural Information Systems (NeurIPS) Workshops, Montreal, QC, Canada, 2018. Online Link
  4. K. En Low, L. Jimenez-Juan, Y. Ung, J. Zhang, F. Khalvati, A. Oikonomou, M. A. Haider. “CT Texture Features as Predictor of Recurrence in Esophageal Cancer Patients Undergoing Trimodality Treatment.” Proceedings of Royal College of Radiologists Conference (RCR), Liverpool, UK, 2018. 
  5. F. Khalvati, E. M. Lobo-Mueller, S. Gallinger, M. A. Haider. “Semi-Automated Radiomic Characterization of Pancreatic Ductal Adenocarcinoma in CT Images.” Proceedings of International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Honolulu, HI, USA, 2018. 

2017

  1. Y. Zhang, A. Oikonomou, A. Wong, M. A. Haider, F. Khalvati. “Radiomics-based Prognosis Analysis for Non-Small Cell Lung Cancer.” Nature Scientific Reports, 7, 46349, 2017. Selected Among Editor’s Choice in Sep 2019. Online Link
  2. T. Clark, J. Zhang, S. Baig, A. Wong, M. A. Haider, F. Khalvati. “Fully Automated Segmentation of Prostate Whole Gland and Transition Zone in Diffusion-weighted MRI using Convolutional Networks.” Journal of Medical Imaging, Vol. 4, No. 4:041307, 2017. Online Link 
  3. M. J. Shafiee, A. G. Chung, F. Khalvati, M. A. Haider, A. Wong. “Discovery Radiomics via Evolutionary Deep Radiomic Sequencer Discovery for Pathologically-Proven Lung Cancer Detection.” Journal of Medical Imaging, Vol. 4, No. 4:041305, 2017. Online Link 
  4. A. Eilaghi, S. Baig, Y. Zhang, J. Zhang, P. Karanicolas, S. Gallinger, F. Khalvati, M. A. Haider. “CT Texture Features are Associated with Overall Survival in Pancreatic Ductal Adenocarcinoma.” BMC Medical Imaging, 2017. Online Link 
  5. M. A. Haider, A. Vosough, F. Khalvati, A. Kiss, B. Ganeshan, G. Bjarnason. “CT Texture Analysis: A Potential Tool for Prediction of Survival in Patients with Metastatic Clear Cell Carcinoma Treated with Sunitinib.” BMC Cancer Imaging, 2017. Online Link
  6. S. Yoo, M. A. Haider, F. Khalvati. “Estimating Optimal Depth of VGG Net with Tree-Structured Parzen Estimators.” Proceedings of Annual Conference on Vision and Intelligent Systems, Waterloo, ON, Canada, 2017. Online Link 
  7. T. Clark, A. Wong, M. A. Haider, F. Khalvati. “Fully Deep Convolutional Neural Networks for Segmentation of the Prostate Gland in Diffusion-Weighted MR Images.” Proceedings of 14th International Conference on Image Analysis and Recognition (ICIAR), Montreal, QC, Canada, 2017. Online Link 
  8. J. Zhang, S. Baig, A. Wong, M. A. Haider, F. Khalvati. “Segmentation of Prostate in Diffusion MR Images via Clustering.” Proceedings of 14th International Conference on Image Analysis and Recognition (ICIAR), Montreal, QC, Canada, 2017. Online Link 
  9. A. Karimi, A. G. Chung, M. J. Shafiee, F. Khalvati, M. A. Haider, A. Ghodsi, A. Wong. “Discovery Radiomics via a Mixture of Deep ConvNet Sequencers for Multi-Parametric MRI Prostate Cancer Classification.” Proceedings of 14th International Conference on Image Analysis and Recognition (ICIAR), Montreal, QC, Canada, 2017. Online Link 
  10. D. Kumar, A. G. Chung, M. J. Shafiee, F. Khalvati, M. A. Haider, A. Wong. “Discovery Radiomics for Pathologically-Proven Computed Tomography Lung Cancer Prediction.” Proceedings 14th International Conference on Image Analysis and Recognition (ICIAR), Montreal, QC, Canada, 2017. Online Link 
  11. D. S. Cho, F. Khalvati, D. Clausi, A. Wong. “A Machine Learning-Driven Approach to Computational Physiological Modeling of Skin Cancer.” Proceedings of 14th International Conference on Image Analysis and Recognition (ICIAR), Montreal, QC, Canada, 2017. Online Link
  12. F. Khalvati, Y. Zhang, S. Baig, P. Karanicolas, S. Gallinger, M. A. Haider. “A Study of Prognostic Value of CT Radiomic Features in Pancreatic Ductal Adenocarcinoma Across Two Centers.” Proceedings of Annual Meeting and Exhibition of the Radiological Society of North America (RSNA), Chicago, IL, USA, 2017. 
  13. F. Khalvati, J. Zhang, S. Baig, A. Wong, M. A. Haider. “Flipping the Computer Aided Diagnosis (CAD) Training Paradigm for Prostate Cancer: Using PI-RADS Reporting of Multi-Parametric MRI (mpMRI) to Train a CAD System and then Validating with Pathology.” Proceedings of 15th Imaging Network Ontario (ImNO) Symposium, London, ON, Canada, 2017. 
  14. A. Karimi, A. G. Chung, M. J. Shafiee, F. Khalvati, M. A. Haider, A. Ghodsi, A. Wong. “Discovery Radiomics via a Mixture of Expert Sequencers using Layered Random Projections (LaRP) for Prostate Cancer Classification.” Proceedings of 15th Imaging Network Ontario (ImNO) Symposium, London, ON, Canada, 2017. 
  15. D. Kumar, V. Menkovski, F. Khalvati, M. A. Haider, A. Wong. “Deep Medical Imaging Visualization for Clinical Decision Support.” Proceedings of 15th Imaging Network Ontario (ImNO) Symposium, London, ON, Canada, 2017. 
  16. A. Eilaghi, M. A. Haider, Y. Zhang, A. Oikonomou, L. JimenezJuan, F. Khalvati. “Radiomics Features Provide Reliable Measurements from Manual Contouring of Tumours in Lung Cancer.” Proceedings of European Congress of Radiology (ECR), Vienna, Austria, 2017. 
  17. R. Al Umairi, F. Mahmood, F. Khalvati, B. Xu, M. Yusishen, L. Jimenez-Juan, M. A. Haider, A. Oikonomou. “Can Radiomics at CT and staging PET/CT Serve as an Imaging Biomarker of EGFR and ALK Alterations in Lung Adenocarcinoma?” Proceedings of World Congress of Thoracic Imaging, Boston, MA, USA, 2017. 

2016

  1. F. Khalvati, A. Salmanpour, S. Rahnamayan, M. A. Haider, H. R. Tizhoosh. “Sequential Registration-Based Segmentation of the Prostate Gland in MR Image Volumes.” Journal of Digital Imaging, Vol. 29, pp. 254-263, 2016. Online Link 
  2. A. Cameron, F. Khalvati, M. A. Haider, A. Wong. “MAPS: A Quantitative Radiomics Approach for Prostate Cancer Detection.” IEEE Transactions on Biomedical Engineering, Vol. 63, No. 6, pp. 1145-1156, 2016. Online Link 
  3. E. Li, F. Khalvati, M. J. Shafiee, M. A. Haider, A. Wong. “Sparse Reconstruction of Compressive Sensing MRI Using Cross-Domain Stochastically Fully Connected Conditional Random Field.” BMC Medical Imaging, 2016. Online Link 
  4. A. Boroomand, M. J. Shafiee, F. Khalvati, M. A. Haider, A. Wong. “Noise-Compensated, Bias-Corrected Diffusion Weighted Endorectal Magnetic Resonance Imaging via a Stochastically Fully-Connected Joint Conditional Random Field Model.” IEEE Transactions on Medical Imaging, Vol. 35, No. 12, pp. 2587-2597, 2016. Online Link 
  5. H. R. Tizhoosh, F. Khalvati. “Method and System for Binary and Quasi-Binary Atlas-Based Auto-Contouring of Volume Sets in Medical Images.” Patent No: US 9,361,701 B2, (Granted), 2016. Online Link
  6. F. Khalvati, J. Zhang, S. Baig, M. A. Haider, A. Wong. “Sparse Correlated Diffusion Imaging: A New Computational Diffusion MRI for Prostate Cancer Detection.” Proceedings of Annual Conference on Vision and Intelligent Systems, Waterloo, ON, Canada, 2016. Won Synaptive Best Imaging Paper Award. Online Link
  7. J. Zhang, S. Baig, A. Wong, M. A. Haider, F. Khalvati. “A Local ROI-specific Atlas-based Segmentation of Prostate Gland and Transitional Zone in Diffusion MRI.” Proceedings of Annual Conference on Vision and Intelligent Systems, Waterloo, ON, Canada, 2016. Online Link 
  8. F. Khalvati, J. Zhang, A. Wong, M. A. Haider. “Bag of Bags: Nested Multi Instance Classification for Prostate Cancer Detection.” Proceedings of IEEE International Conference on Machine Learning and Applications (ICMLA), Anaheim, CA, USA, 2016. Online Link 
  9. F. Khalvati, J. Zhang, M. A. Haider, A. Wong. “Enhanced Dual-Stage Correlated Diffusion Imaging.” Proceedings of International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, FL, USA, 2016. Online Link 
  10. A. Boroomand, E. Li, M. J. Shafiee, M. A. Haider, F. Khalvati, A. Wong. “A Unified Bayesian-based Compensated Magnetic Resonance Imaging.” Proceedings of International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, FL, USA, 2016. Online Link 
  11. A. Eilaghi, F. Khalvati, S. Baig, S. Gallinger, P. Karanicolas, M. A. Haider. “CT Texture Parameters are Promising Prognostic Biomarkers in Pancreatic Ductal Adenocarcinoma.” Proceedings of Annual Meeting and Exhibition of the Radiological Society of North America (RSNA), Chicago, IL, USA, 2016. 
  12. Y. Zhang, A. Eilaghi, A. Wong, A. Oikonomou, M. A. Haider, F. Khalvati. “Radiomics Feature Clusters and Prognostic Signatures Specific for Lung Cancer.” Proceedings of 14th Imaging Network Ontario (ImNO) Symposium, Toronto, ON, Canada, 2016. 
  13. J. Zhang, A. Eilaghi, M. A. Haider, A. Wong, F. Khalvati. “Optimized Correlated Diffusion Imaging for Prostate Cancer Detection.” Proceedings of 14th Imaging Network Ontario (ImNO) Symposium, Toronto, ON, Canada, 2016. 
  14. A. Eilaghi, S. Baig, J. Zhang, A. Wong, P. Karanicolas, S. Gallinger, F. Khalvati, M. A. Haider. “Radiomics Features Analysis for Tumor Characterization in Pancreatic Ductal Adenocarcinoma.” Proceedings of 14th Imaging Network Ontario (ImNO) Symposium, Toronto, ON, Canada, 2016. Won Magnum Cum Laude Paper Award
  15. A. Boroomand, E. Li, M. J. Shafiee, F. Khalvati, M. A. Haider, A. Wong. “A Unified Reconstruction Framework for Compensated Magnetic Resonance Imaging”, Proceedings of 14th Imaging Network Ontario (ImNO) Symposium, Toronto, ON, Canada, 2016. 
  16. A. G. Chung, M. J. Shafiee, D. Kumar, F. Khalvati, M. A. Haider, A. Wong. “Discovery Radiomics via Layered Random Projection (LaRP) Sequencers for Prostate Cancer Classification.” Proceedings of 14th Imaging Network Ontario (ImNO) Symposium, Toronto, ON, Canada, 2016. Won Magnum Cum Laude Paper Award. 
  17. D. Kumar, M. J. Shafiee, A. G. Chung, F. Khalvati, M. A. Haider, A. Wong. “Discovery Radiomics for Lung Cancer Classification.” Proceedings of 14th Imaging Network Ontario (ImNO) Symposium, Toronto, ON, Canada, 2016. 
  18. S. A. Haider, A. G. Chung, M. J. Shafiee, H. Grewal, F. Khalvati, A. Oikonomou, M. A. Haider, A. Wong. “Single-Click Lung Nodule Contouring Method Using a Hierarchical Conditional Random Field (HCRF).” Proceedings of 14th Imaging Network Ontario (ImNO) Symposium, Toronto, ON, Canada, 2016. 
  19. A. Oikonomou, F. Khalvati, U. Tarique, L. Jimenez-Juan, G. Tomlinson, C. Caldwell, M. A. Haider, P. Cheung. “Texture Analysis of Early Stage Lung Cancer on Positron Emission Tomography/ Computed Tomography (PET/CT) as a Predictor of Clinical Outcome post Stereotactic Body Radiotherapy (SBRT).” Proceedings of Annual Meeting of Society of Thoracic Radiology, Scottsdale, AZ, USA, 2016. 

2015

  1. F. Khalvati, C. Gallego Ortiz, S. Balasingham, A. L. Martel. “Automated Segmentation of Breast in 3D MR Images Using a Robust Atlas.” IEEE Transactions on Medical Imaging, Vol. 34, No. 1, pp. 116-125, 2015. Online Link 
  2. F. Khalvati, A. Wong, M. A. Haider. “Automated Prostate Cancer Detection via Comprehensive Multi-Parametric Magnetic Resonance Imaging Texture Feature Models.” BMC Medical Imaging, pp. 15-27, 2015. Online Link
  3. F. Khalvati, M. D. Aagaard, H. R. Tizhoosh. “Window Memoization: Toward High-Performance Image Processing Software.” Journal of Real-Time Image Processing, Vol. 10, No. 1, pp. 5-25, 2015. Online Link
  4. A. G. Chung, F. Khalvati, M. J. Shafiee, M. A. Haider, A. Wong. “Prostate Cancer Detection via a Quantitative Radiomics-Driven Conditional Random Field Framework.” IEEE Access, Vol. 3, pp. 2531-2541, 2015. Online Link
  5. F. Khalvati, H. R. Tizhoosh. “System, Method and Computer Program for Automated Window Memoization.” Patent No: US 9,076,240 B2, 2015 (Granted). Online Link  
  6. M. J. Shafiee, A. G. Chung, D. Kumar, A. Wong, F. Khalvati, M. A. Haider. “Discovery Radiomics via StochasticNet Sequencers for Cancer Detection.” Proceedings of International Conference on Neural Information Systems (NIPS) Workshops, Montreal, QC, Canada, 2015. Online Link 
  7. A. Othman, H. R. Tizhoosh, F. Khalvati. “Self-Configuring and Evolving Fuzzy Image Thresholding.” Proceedings of IEEE International Conference on Machine Learning and Applications (ICMLA), Miami, FL, USA, 2015. Online Link
  8. Z. Camlica, H. R. Tizhoosh, F. Khalvati. “Medical Image Classification via SVM using LBP Features from Saliency-Based Folded Data.” Proceedings of IEEE International Conference on Machine Learning and Applications (ICMLA), Miami, FL, USA, 2015. Online Link 
  9. Z. Camlica, H. R. Tizhoosh, F. Khalvati. “Autoencoding the Retrieval Relevance of Medical Images.” Proceedings of IEEE International Conference on Image Processing, Tools, Theory and Applications (IPTA), Orleans, France, 2015. Online Link 
  10. A. G. Chung, C. Scharfenberger, F. Khalvati, A. Wong, M. A. Haider. “Statistical Textural Distinctiveness in Multi-Parametric Prostate MRI for Suspicious Region Detection.” Proceedings of International Conference on Image Analysis and Recognition (ICIAR), Niagara Falls, ON, Canada, 2015. Online Link 
  11. A. Wong, F. Khalvati, M. A. Haider. “Dual-Stage Correlated Diffusion Imaging.” Proceedings of IEEE International Symposium on Biomedical Imaging (ISBI), Brooklyn, NY, USA, 2015. Online Link 
  12. S. A. Haider, M. J. Shafiee, A. G. Chung, F. Khalvati, A. Oikonomou, A. Wong, M. A. Haider. “Single-Click, Semi-Automatic Lung Nodule Contouring Using Hierarchical Conditional Random Fields. “Proceedings of IEEE International Symposium on Biomedical Imaging (ISBI), Brooklyn, NY, USA, 2015. Online Link 
  13. J. Zhang, Khalvati, A. Wong, M. A. Haider. “Superpixel-based Prostate Cancer Detection from Diffusion Magnetic Resonance Imaging.” Proceedings of Conference on Vision and Imaging Systems, Waterloo, ON, Canada, 2015. 
  14. E. Li, M. J. Shafiee, A. Boroomand, F. Khalvati, M. A. Haider, A. Wong. “Compensated Diffusion Magnetic Resonance Imaging.” Proceedings of Conference on Vision and Imaging Systems, Waterloo, ON, Canada, 2015. 
  15. A. Wong, A. G. Chung, D. Kumar, M. J. Shafiee, F. Khalvati, M. A. Haider. “Discovery Radiomics for Imaging-driven Quantitative Personalized Cancer Decision Support.” Proceedings of Conference on Vision and Imaging Systems, Waterloo, ON, Canada, 2015. 
  16. C. Scharfenberger, D. Lui, F. Khalvati, A. Wong, M. A. Haider. “Semi-Automatic Prostate Segmentation via a Hidden Markov Model with Anatomical and Textural Priors.” Proceedings of Annual Meeting and Exhibition of International Society for Magnetic Resonance in Medicine (ISMRM), Toronto, ON, Canada, 2015.
  17. E. Li, M. J. Shafiee, A. G. Chung, F. Khalvati, A. Wong, M. A. Haider. “Enhanced Reconstruction of Compressive Sensing MRI via Cross-Domain Stochastically Fully-Connected Random Field Model.” Proceedings of Annual Meeting and Exhibition International Society for Magnetic Resonance in Medicine (ISMRM), Toronto, ON, Canada, 2015. 
  18. A. Boroomand, M. J. Shafiee, A. Wong, F. Khalvati, P. Fieguth, M. A. Haider. “Noise-Compensated Bias Correction of MRI via a Stochastically Fully-Connected Conditional Random Field Model.” Proceedings of Annual Meeting and Exhibition of International Society for Magnetic Resonance in Medicine (ISMRM), Toronto, ON, Canada, 2015. 
  19. D. S. Cho, F. Khalvati, A. Wong, D. A. Clausi, M. A. Haider. “Prostate DWI Co-Registration via Maximization of Hybrid Statistical Likelihood and Cross-Correlation for Improved ADC and Computed Ultra-High b-value DWI Calculation.” Proceedings of Annual Meeting and Exhibition of International Society for Magnetic Resonance in Medicine (ISMRM), Toronto, ON, Canada, 2015. 
  20. A. Oikonomou, U. Tarique, L. Jimenez-Juan, F. Khalvati, L. Ehrlich, G. Tomlinson, M. A. Haider, P. Cheung. “Tumor Heterogeneity and Intensity of Early Stage Lung Cancer on PET and Computed Tomography as a Predictor of Response to Stereotactic Body Radiotherapy (SBRT).” Proceedings of Annual Meeting of Society of Thoracic Radiology, Carlsbad, CA, USA, 2015. 

2014

  1. A. Othman, H. R. Tizhoosh, F. Khalvati. “EFIS-Evolving Fuzzy Image Segmentation.” IEEE Transactions on Fuzzy Systems, Vol. 22, No. 1, pp. 72-82, 2014. Online Link
  2. F. Khalvati, A. Modhafar, A. Cameron, A. Wong, M. A. Haider. “A Multi-Parametric Diffusion Magnetic Resonance Imaging Texture Feature Model for Prostate Cancer Analysis.” Proceedings of International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) Workshops, Boston, MA, USA, 2014. Online Link 
  3. A. Cameron, A. Modhafar, F. Khalvati, D. Lui, M. J. Shafiee, A. Wong, M. A. Haider. “Multi-Parametric MRI Prostate Cancer Analysis via a Hybrid Morphological-Textural Model.” Proceedings of International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Chicago, IL, USA, 2014. Online Link
  4. F. Khalvati, A. Wong, G. A. Bjarnason, M. A. Haider. “Semi-Automatic Normalized Entropy Characterization of Metastatic Renal Cell Cancer via Spatio-Textural Tumour Classification.” Proceedings of International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Chicago, IL, USA, 2014.  

2013

  1. F. Khalvati, A. Salmanpour, S. Rahnamayan, G. Rodrigues, H. R. Tizhoosh. “Inter-Slice Bidirectional Registration-Based Segmentation of the Prostate Gland in MR and CT Image Sequences.” Medical Physics, Vol. 40, No.12, pp.123503-1-11, 2013. Online Link 
  2. S. Martin, G. Rodrigues, N. Patil, G. Bauman, D. D’Souza, T. Sexton, D. Palma, A. V. Louie, F. Khalvati, H. R. Tizhoosh, S. Gaede. “A Multi-Phase Validation of Atlas-Based Automatic and Semi-Automatic Segmentation Strategies for Prostate MRI.” International Journal of Radiation Oncology, Biology, Physics. Vol. 85, No. 1, pp. 95-100, 2013. Online Link 
  3. H. R. Tizhoosh, F. Khalvati. “Computer System and Method for Atlas-Based Consensual and Consistent Contouring of Medical Images.” International Publication Number: WO 2013/040693 A1, 2013 (Filed). Online Link
  4.  F. Khalvati, A. L. Martel. “Atlas-Based Segmentation of Breast MR Images.” Proceedings of International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) Workshops, Nagoya, Japan, 2013. Online Link 

<2012

  1. F. Khalvati, M. D. Aagaard. “Window Memoization: An Efficient Hardware Architecture for High-Performance Image Processing.” Journal of Real-Time Image Processing, Vol. 5, No. 3, pp. 195-212, 2010. Online Link 
  2. F. Khalvati, M. Kianpour, H. R. Tizhoosh. “Cascaded Window Memoization for Medical Imaging.” Proceedings of International Conference on Artificial Intelligence Applications and Innovations (AIAI), Corfu, Greece, 2011. Online Link 
  3. F. Khalvati, H. R. Tizhoosh. “Perfect Window Memoization: A Theoretical Model of an Optimization Technique for Image Processing Algorithms.” Proceedings of International Conference on Image Processing, Computer Vision, and Pattern Recognition (IPCV), Las Vegas, NV, USA, 2011. Online Link 
  4. S. Martin, N. Patil, S. Gaede, A. Louie, G. Bauman, D. D’Souza, T. Sexton, D. Palma, F. Khalvati, G. Rodrigues. “A Multi-phase Technological Validation of a MRI Prostate Cancer Computer Autosegmentation Software Algorithm.” Proceedings of American Society for Therapeutic Radiology and Oncology (ASTRO) Annual meeting, Miami Beach, FL, USA, 2011. 
  5. F. Khalvati, H. R. Tizhoosh, A. R. Hajian. “Increasing Computational Redundancy of Digital Images via Multiresolutional Matching.” Proceedings of International Conference on Image Analysis and Recognition (ICIAR), Halifax, NS, Canada, 2009. Online Link 
  6. F. Khalvati, H. R. Tizhoosh. “An Efficient Architecture for Hardware Implementations of Image Processing Algorithms.” Proceedings of IEEE Symposium on Computational Intelligence for Image Processing (CIIP), Nashville, TN, USA, 2009. Online Link 
  7. F. Khalvati. “Computational Redundancy in Image Processing.” Ph.D. Thesis, University of Waterloo, Waterloo, ON, Canada, 2008. Online Link 
  8. F. Khalvati, M. D. Aagaard, H. R. Tizhoosh. “Accelerating Image Processing Algorithms Based on the Reuse of Spatial Patterns.” Proceedings of Canadian Conference on Electrical and Computer Engineering (CCECE), Vancouver, BC, Canada, 2007. Online Link 
  9. F. Khalvati, H. R. Tizhoosh, M. D. Aagaard. “Opposition-Based Window Memoization for Morphological Algorithms.” Proceedings of IEEE Symposium on Computational Intelligence in Image and Signal Processing (CIISP), Honolulu, HI, USA, 2007. Won IEEE Outstanding Student-Paper Travel Award. Online Link 
  10. M. F. Baroughi, R. Jayakumar, Y. Vygranenko, F. Khalvati, S. Sivoththaman. “Fabrication and Characterization of Amorphous Si/Crystalline Si Heterojunction Devices for Photovoltaic Applications.” Journal of Vacuum Science & Technology A: Vacuum, Surfaces, and Films, Vol. 22, No. 3, pp. 1015-1019, 2004. Online Link 
  11. M. D. Aagaard, V. C. Ciubotariu, J. T. Higgins, F. Khalvati. “Combining Equivalence Verification and Completion Functions.” Proceedings of Formal Methods in Computer-Aided Design (FMCAD), Austin, TX, USA, 2004. Online Link 
  12. F. Khalvati, S. Sivoththaman. “Quantum Efficiency Modeling of Amorphous /Crystalline Silicon Heterojunction Photovoltaic Devices.” Proceedings of Material Research Society Symposium (MRS), Boston, MA, USA, 2003. 
  13. F. Khalvati. “Modeling and Analysis of Amorphous Si/Crystalline Si Heterojunction Photovoltaic Cells.” M.A.Sc. Thesis, University of Waterloo, Waterloo, ON, Canada, 2003. Online Link