F. Khalvati

发表

CT texture analysis: a potential tool for prediction of survival in patients with metastatic clear cell carcinoma treated with sunitinib

M. Haider, B. Ganeshan, G. Bjarnason, 2017, Cancer Imaging.

Discovery Radiomics for Pathologically-Proven Computed Tomography Lung Cancer Prediction

Masoom A. Haider, Alexander Wong, Farzad Khalvati, 2015, ICIAR.

Radiomics analysis at PET/CT contributes to prognosis of recurrence and survival in lung cancer treated with stereotactic body radiotherapy

Farzad Khalvati, Ian Poon, Masoom A Haider, 2018, Scientific Reports.

Prognostic value of early changes in CT-measured body composition in patients receiving chemotherapy for unresectable pancreatic cancer

M. Haider, V. Baracos, S. Gallinger, 2021, European Radiology.

A Local ROI-specific Atlas-based Segmentation of Prostate Gland and Transitional Zone in Diffusion MRI

Masoom A. Haider, Alexander Wong, Farzad Khalvati, 2016 .

Inter-slice bidirectional registration-based segmentation of the prostate gland in MR and CT image sequences.

Shahryar Rahnamayan, Farzad Khalvati, Hamid R Tizhoosh, 2013, Medical physics.

Superpixel-based Prostate Cancer Detection from Diffusion Magnetic Resonance Imaging

Masoom A. Haider, Alexander Wong, Farzad Khalvati, 2015 .

Can machine learning radiomics provide pre-operative differentiation of combined hepatocellular cholangiocarcinoma from hepatocellular carcinoma and cholangiocarcinoma to inform optimal treatment planning?

M. Haider, B. Taouli, K. Jhaveri, 2020, European Radiology.

Using decision curve analysis to benchmark performance of a magnetic resonance imaging–based deep learning model for prostate cancer risk assessment

M. Haider, L. Milot, F. Khalvati, 2020, European Radiology.

Perfect Window Memoization : A Theoretical Model of an Optimization Technique for Image Processing Algorithms

H. Tizhoosh, F. Khalvati, 2011 .

Validation of Prognostic Radiomic Features From Resectable Pancreatic Ductal Adenocarcinoma in Patients With Advanced Disease Undergoing Chemotherapy

M. Haider, S. Gallinger, J. Knox, 2020, Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes.

Radiomic Features Based on MRI Predict Progression-Free Survival in Pediatric Diffuse Midline Glioma/Diffuse Intrinsic Pontine Glioma

B. Ertl-Wagner, M. Shroff, U. Bartels, 2022, Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes.

Atlas-Based Segmentation of Breast MR Images

Anne L. Martel, F. Khalvati, 2014 .

D ATA A UGMENTATION USING G ENERATIVE A DVERSARIAL N ETWORKS (GAN S ) FOR GAN- BASED D ETECTION OF P NEUMONIA AND COVID-19 IN C HEST X- RAY I MAGES

P. Rogalla, F. Khalvati, Saman Motamed, 2021 .

Improving disease classification performance and explainability of deep learning models in radiology with heatmap generators

F. Khalvati, Khashayar Namdar, A. Watanabe, 2022, Frontiers in Radiology.

Data governance functions to support responsible data stewardship in pediatric radiology research studies using artificial intelligence

Melissa D. McCradden, Birgit B Ertl-Wagner, A. Biswas, 2022, Pediatric Radiology.

Superpixel Generation and Clustering for Weakly Supervised Brain Tumor Segmentation in MR Images

F. Khalvati, Khashayar Namdar, Jayeon Yoo, 2022, ArXiv.

Introducing Vision Transformer for Alzheimer's Disease classification task with 3D input

F. Khalvati, Zilun Zhang, 2022, 2210.01177.

An Educational Graphical User Interface to Construct Convolutional Neural Networks for Teaching Artificial Intelligence in Radiology

Haiyue Jin, F. Khalvati, M. Wagner, 2022, Canadian Association of Radiologists Journal.

A Comprehensive Study of Radiomics-based Machine Learning for Fibrosis Detection

P. Rogalla, C. McIntosh, F. Khalvati, 2022, ArXiv.

Relevance maps: A weakly supervised segmentation method for 3D brain tumours in MRIs

F. Khalvati, Sajith Rajapaksa, 2022, Frontiers in Radiology.

Automated Segmentation of Breast in 3-D MR Images Using a Robust Atlas

Farzad Khalvati, Anne L. Martel, Cristina Gallego-Ortiz, 2015, IEEE Transactions on Medical Imaging.

Value of Increasing Biopsy Cores per Target with Cognitive MRI-targeted Transrectal US Prostate Biopsy.

M. Haider, L. Klotz, L. Milot, 2019, Radiology.

Evaluating Knowledge Transfer In Neural Network for Medical Images

E. Dolatabadi, F. Khalvati, Sina Akbarian, 2020, ArXiv.

Radiomics, machine learning, and artificial intelligence—what the neuroradiologist needs to know

B. Ertl-Wagner, A. Biswas, F. Khalvati, 2021, Neuroradiology.

Radiomics of Pediatric Low-Grade Gliomas: Toward a Pretherapeutic Differentiation of BRAF-Mutated and BRAF-Fused Tumors

K. Yeom, C. Hawkins, B. Ertl-Wagner, 2021, American Journal of Neuroradiology.

A Pre-TACE Radiomics Model to Predict HCC Progression and Recurrence in Liver Transplantation: A Pilot Study on a Novel Biomarker

M. Haider, P. Veit-Haibach, K. Jhaveri, 2021, Transplantation.

Improving prognostic performance in resectable pancreatic ductal adenocarcinoma using radiomics and deep learning features fusion in CT images

Masoom A. Haider, Yucheng Zhang, Farzad Khalvati, 2019, Scientific Reports.

Radiomics-based Prognosis Analysis for Non-Small Cell Lung Cancer

Masoom A. Haider, Alexander Wong, Farzad Khalvati, 2017, Scientific Reports.

CT texture features are associated with overall survival in pancreatic ductal adenocarcinoma – a quantitative analysis

Masoom A. Haider, Yucheng Zhang, Farzad Khalvati, 2017, BMC Medical Imaging.

Segmentation of Prostate in Diffusion MR Images via Clustering

Masoom A. Haider, Alexander Wong, Farzad Khalvati, 2017, ICIAR.

Automated prostate cancer detection via comprehensive multi-parametric magnetic resonance imaging texture feature models

Masoom A. Haider, Alexander Wong, Farzad Khalvati, 2015, BMC Medical Imaging.

Tumor-location-guided CNNs for Pediatric Low-grade Glioma Molecular Biomarker Classification Using MRI

C. Hawkins, U. Tabori, F. Khalvati, 2022, ArXiv.

Dual-stage correlated diffusion imaging

Masoom A. Haider, Alexander Wong, Farzad Khalvati, 2015, 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI).

Prostate Cancer Detection using Deep Convolutional Neural Networks

Masoom A. Haider, Farzad Khalvati, Isha Gujrathi, 2019, Scientific Reports.

Radiomics analysis at PET/CT contributes to prognosis of recurrence and survival in lung cancer treated with stereotactic body radiotherapy

M. Haider, I. Poon, P. Cheung, 2018, Scientific Reports.

Discovery Radiomics for Computed Tomography Cancer Detection pdf

Masoom A. Haider, Alexander Wong, Farzad Khalvati, 2015, ArXiv.

A Brief Review of Deep Multi-task Learning and Auxiliary Task Learning pdf

Khashayar Namdar, Farzad Khalvati, Partoo Vafaeikia, 2020, ArXiv.

Discovery Radiomics via StochasticNet Sequencers for Cancer Detection pdf

Masoom A. Haider, Alexander Wong, Farzad Khalvati, 2015, ArXiv.

A Comprehensive Study of Data Augmentation Strategies for Prostate Cancer Detection in Diffusion-Weighted MRI Using Convolutional Neural Networks pdf

Lin Liu, Ruqian Hao, Khashayar Namdar, 2020, Journal of Digital Imaging.

Noise-Compensated, Bias-Corrected Diffusion Weighted Endorectal Magnetic Resonance Imaging via a Stochastically Fully-Connected Joint Conditional Random Field Model

Masoom A. Haider, Alexander Wong, Farzad Khalvati, 2015, IEEE Transactions on Medical Imaging.

Open-radiomics: A Research Protocol to Make Radiomics-based Machine Learning Pipelines Reproducible

Birgit B Ertl-Wagner, F. Khalvati, M. Wagner, 2022, ArXiv.

A Transfer Learning–Based Active Learning Framework for Brain Tumor Classification pdf

Lin Liu, Ruqian Hao, Khashayar Namdar, 2020, Frontiers in Artificial Intelligence.

MPCaD: a multi-scale radiomics-driven framework for automated prostate cancer localization and detection

Masoom A. Haider, Alexander Wong, Farzad Khalvati, 2018, BMC Medical Imaging.

MAPS: A Quantitative Radiomics Approach for Prostate Cancer Detection

Masoom A. Haider, Alexander Wong, Farzad Khalvati, 2016, IEEE Transactions on Biomedical Engineering.

Prostate Cancer Detection via a Quantitative Radiomics-Driven Conditional Random Field Framework

Masoom A. Haider, Alexander Wong, Farzad Khalvati, 2015, IEEE Access.

Fully Deep Convolutional Neural Networks for Segmentation of the Prostate Gland in Diffusion-Weighted MR Images

Masoom A. Haider, Alexander Wong, Farzad Khalvati, 2017, ICIAR.

Medical Image Classification via SVM Using LBP Features from Saliency-Based Folded Data

Hamid R. Tizhoosh, Farzad Khalvati, Zehra Camlica, 2015, 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA).

Prognostic Value of Transfer Learning Based Features in Resectable Pancreatic Ductal Adenocarcinoma

Masoom A. Haider, Yucheng Zhang, Farzad Khalvati, 2019, Frontiers in Artificial Intelligence.

CNN-based survival model for pancreatic ductal adenocarcinoma in medical imaging

Masoom A. Haider, Yucheng Zhang, Farzad Khalvati, 2019, BMC Medical Imaging.

Prognostic Value of CT Radiomic Features in Resectable Pancreatic Ductal Adenocarcinoma

Farzad Khalvati, Edrise M. Lobo-Mueller, Paul Karanicolas, 2019, Scientific Reports.

A Modified AUC for Training Convolutional Neural Networks: Taking Confidence Into Account

Masoom A. Haider, Farzad Khalvati, Khashayar Namdar, 2020, Frontiers in Artificial Intelligence.

Self-Configuring and Evolving Fuzzy Image Thresholding

Hamid R. Tizhoosh, Farzad Khalvati, Ahmed A. Othman, 2015, 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA).

Evolving Fuzzy Image Segmentation with Self-Configuration pdf

Hamid R. Tizhoosh, Farzad Khalvati, Ahmed A. Othman, 2015, ArXiv.

EFIS—Evolving Fuzzy Image Segmentation

Hamid R. Tizhoosh, Farzad Khalvati, Ahmed A. Othman, 2014, IEEE Transactions on Fuzzy Systems.

Prognostic Value of CT Radiomic Features in Resectable Pancreatic Ductal Adenocarcinoma

M. Haider, S. Gallinger, P. Karanicolas, 2019, Scientific Reports.

Window memoization: toward high-performance image processing software

H. Tizhoosh, M. Aagaard, F. Khalvati, 2015, Journal of Real-Time Image Processing.

Window memoization: an efficient hardware architecture for high-performance image processing

Farzad Khalvati, Mark Aagaard, M. Aagaard, 2010, Journal of Real-Time Image Processing.

An efficient architecture for hardware implementations of image processing algorithms

Hamid R. Tizhoosh, Farzad Khalvati, H. Tizhoosh, 2009, 2009 IEEE Symposium on Computational Intelligence for Image Processing.

Computational Redundancy in Image Processing

Farzad Khalvati, F. Khalvati, 2008 .

Accelerating Image Processing Algorithms Based on the Reuse of Spatial Patterns

F. Khalvati, H.R. Tizhoosh, M.D. Aagaard, 2007, 2007 Canadian Conference on Electrical and Computer Engineering.

Improving Prognostic Value of CT Deep Radiomic Features in Pancreatic Ductal Adenocarcinoma Using Transfer Learning pdf

Masoom A. Haider, Yucheng Zhang, Farzad Khalvati, 2019, ArXiv.

PI-RADS guided discovery radiomics for characterization of prostate lesions with diffusion-weighted MRI

Masoom A. Haider, Farzad Khalvati, Yucheng Zhang, 2019, Medical Imaging.

Fully automated segmentation of prostate whole gland and transition zone in diffusion-weighted MRI using convolutional neural networks

Alexander Wong, Farzad Khalvati, Junjie Zhang, 2017, Journal of medical imaging.

Data augmentation using Generative Adversarial Networks (GANs) for GAN-based detection of Pneumonia and COVID-19 in chest X-ray images

Patrik Rogalla, Farzad Khalvati, Saman Motamed, 2021, Informatics in Medicine Unlocked.

Using Large Text To Image Models with Structured Prompts for Skin Disease Identification: A Case Study

Jean M. Uwabeza Vianney, F. Khalvati, Sajith Rajapaksa, 2023, 2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW).

A Machine Learning-Driven Approach to Computational Physiological Modeling of Skin Cancer

David A. Clausi, Daniel S. Cho, Alexander Wong, 2017, ICIAR.

Hepatocellular adenoma subtyping by qualitative MRI features and machine learning algorithm of integrated qualitative and quantitative features: a proof-of-concept study.

K. Jhaveri, O. Espin-Garcia, F. Khalvati, 2023, Clinical radiology.

Reducing Unnecessary Prostate Multiparametric Magnetic Resonance Imaging by Using Clinical Parameters to Predict Negative and Indeterminate Findings

M. Haider, Yucheng Zhang, F. Khalvati, 2020 .

MRI-Based End-To-End Pediatric Low-Grade Glioma Segmentation and Classification

U. Tabori, F. Khalvati, C. Hawkins, 2023, Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes.

Sparse reconstruction of compressive sensing MRI using cross-domain stochastically fully connected conditional random fields

Masoom A. Haider, Alexander Wong, Farzad Khalvati, 2015, BMC Medical Imaging.

RANDGAN: Randomized generative adversarial network for detection of COVID-19 in chest X-ray pdf

Farzad Khalvati, Saman Motamed, Patrik Rogalla, 2020, Scientific Reports.

Estimating Optimal Depth of VGG Net with Tree-Structured Parzen Estimators

Masoom A. Haider, Farzad Khalvati, Sunghwan Yoo, 2017 .

Towards Reducing Overutilization of Prostate mpMRI: Using Clinical Parameters to Predict Negative and Indeterminate mpMRI Scans.

M. Haider, Yucheng Zhang, F. Khalvati, 2019, Journal of Urology.

Autoencoding the retrieval relevance of medical images

Hamid R. Tizhoosh, Farzad Khalvati, Zehra Camlica, 2015, 2015 International Conference on Image Processing Theory, Tools and Applications (IPTA).

Enhanced dual-stage correlated diffusion imaging

Masoom A. Haider, Alexander Wong, Farzad Khalvati, 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Discovery Radiomics for Multi-Parametric MRI Prostate Cancer Detection pdf

Masoom A. Haider, Alexander Wong, Farzad Khalvati, 2015, ArXiv.

Statistical Textural Distinctiveness in Multi-Parametric Prostate MRI for Suspicious Region Detection

Masoom A. Haider, Alexander Wong, Farzad Khalvati, 2015, ICIAR.

A Multi-Parametric Diffusion Magnetic Resonance Imaging Texture Feature Model for Prostate Cancer Analysis

Masoom A. Haider, Alexander Wong, Farzad Khalvati, 2014 .

Radiomics Driven Diffusion Weighted Imaging Sensing Strategies for Zone-Level Prostate Cancer Sensing

Alexander Wong, Farzad Khalvati, Linda Wang, 2020, Sensors.

T2-FLAIR Mismatch Sign in Pediatric Low-Grade Glioma

U. Tabori, F. Khalvati, L. Nobre, 2023, American Journal of Neuroradiology.

Improving the Segmentation of Pediatric Low-Grade Gliomas Through Multitask Learning pdf

Farzad Khalvati, Uri Tabori, Partoo Vafaeikia, 2021, 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

A novel GAN-based paradigm for weakly supervised brain tumor segmentation of MR images

U. Tabori, F. Khalvati, Matthias W. Wagner, 2022, ArXiv.

Optimized Global Perturbation Attacks For Brain Tumour ROI Extraction From Binary Classification Models

F. Khalvati, Sajith Rajapaksa, 2022, ArXiv.

Multiparametric MRI prostate cancer analysis via a hybrid morphological-textural model

Masoom A. Haider, Alexander Wong, Farzad Khalvati, 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Using Multi-modal Data for Improving Generalizability and Explainability of Disease Classification in Radiology

F. Khalvati, Khashayar Namdar, Sara Ketabi, 2022, ArXiv.

Evaluating Knowledge Transfer in the Neural Network for Medical Images

E. Dolatabadi, F. Khalvati, Laleh Seyyed-Kalantari, 2023, IEEE Access.

Cascaded Window Memoization for Medical Imaging

Hamid R. Tizhoosh, Farzad Khalvati, Mehdi Kianpour, 2011, EANN/AIAI.

Generating 3D Brain Tumor Regions in MRI using Vector-Quantization Generative Adversarial Networks

U. Tabori, F. Khalvati, C. Hawkins, 2023, ArXiv.

Deep Superpixel Generation and Clustering for Weakly Supervised Segmentation of Brain Tumors in MR Images

F. Khalvati, Khashayar Namdar, Jayeon Yoo, 2022, 2209.09930.

Exploring COVID-19–Related Stressors: Topic Modeling Study

F. Khalvati, Yue Tong Leung, 2022, Journal of medical Internet research.