Combining Equivalence Verification and Completion Functions. - Mark D. Aagaard; Vlad C. Ciubotariu; Jason T. Higgins; Farzad Khalvati (FMCAD, 2004)

Computational Redundancy in Image Processing. - Farzad Khalvati (2008)

An efficient architecture for hardware implementations of image processing algorithms. - Farzad Khalvati; Hamid R. Tizhoosh (CIIP, 2009)

Increasing Computational Redundancy of Digital Images via Multiresolutional Matching. - Farzad Khalvati; Hamid R. Tizhoosh; Arsen R. Hajian (ICIAR, 2009)

Window memoization: an efficient hardware architecture for high-performance image processing. - Farzad Khalvati; Mark D. Aagaard (J. Real Time Image Process., 2010)

Cascaded Window Memoization for Medical Imaging. - Farzad Khalvati; Mehdi Kianpour; Hamid R. Tizhoosh (AIAI, 2011)

Multiparametric MRI prostate cancer analysis via a hybrid morphological-textural model. - Andrew Cameron; Amen Modhafar; Farzad Khalvati; Dorothy Lui; Mohammad Javad Shafiee; Alexander Wong; Masoom A. Haider (EMBC, 2014)

EFIS - Evolving Fuzzy Image Segmentation. - Ahmed A. Othman; Hamid R. Tizhoosh; Farzad Khalvati (IEEE Trans. Fuzzy Syst., 2014)

Statistical Textural Distinctiveness in Multi-Parametric Prostate MRI for Suspicious Region Detection. - Audrey G. Chung; Christian Scharfenberger; Farzad Khalvati; Alexander Wong; Masoom A. Haider (ICIAR, 2015)

Medical Image Classification via SVM Using LBP Features from Saliency-Based Folded Data. - Zehra Camlica; Hamid R. Tizhoosh; Farzad Khalvati (ICMLA, 2015)

Self-Configuring and Evolving Fuzzy Image Thresholding. - Ahmed A. Othman; Hamid R. Tizhoosh; Farzad Khalvati (ICMLA, 2015)

Autoencoding the retrieval relevance of medical images. - Zehra Camlica; Hamid R. Tizhoosh; Farzad Khalvati (IPTA, 2015)

Single-click, semi-automatic lung nodule contouring using hierarchical conditional random fields. - Shahid A. Haider; Mohammad Javad Shafiee; Audrey G. Chung; Farzad Khalvati; Anastasia Oikonomou; Alexander Wong; Masoom A. Haider (ISBI, 2015)

Dual-stage correlated diffusion imaging. - Alexander Wong; Farzad Khalvati; Masoom A. Haider (ISBI, 2015)

Prostate Cancer Detection via a Quantitative Radiomics-Driven Conditional Random Field Framework. - Audrey G. Chung; Farzad Khalvati; Mohammad Javad Shafiee; Masoom A. Haider; Alexander Wong (IEEE Access, 2015)

Automated prostate cancer detection via comprehensive multi-parametric magnetic resonance imaging texture feature models. - Farzad Khalvati; Alexander Wong; Masoom A. Haider (BMC Medical Imaging, 2015)

Discovery Radiomics for Multi-Parametric MRI Prostate Cancer Detection. - Audrey G. Chung; Mohammad Javad Shafiee; Devinder Kumar; Farzad Khalvati; Masoom A. Haider; Alexander Wong (CoRR, 2015)

Discovery Radiomics for Computed Tomography Cancer Detection. - Devinder Kumar; Mohammad Javad Shafiee; Audrey G. Chung; Farzad Khalvati; Masoom A. Haider; Alexander Wong (CoRR, 2015)

Evolving Fuzzy Image Segmentation with Self-Configuration. - Ahmed A. Othman; Hamid R. Tizhoosh; Farzad Khalvati (CoRR, 2015)

Discovery Radiomics via StochasticNet Sequencers for Cancer Detection. - Mohammad Javad Shafiee; Audrey G. Chung; Devinder Kumar; Farzad Khalvati; Masoom A. Haider; Alexander Wong (CoRR, 2015)

Window memoization: toward high-performance image processing software. - Farzad Khalvati; Mark D. Aagaard; Hamid R. Tizhoosh (J. Real Time Image Process., 2015)

Automated Segmentation of Breast in 3-D MR Images Using a Robust Atlas. - Farzad Khalvati; Cristina Gallego-Ortiz; Sharmila Balasingham; Anne L. Martel (IEEE Trans. Medical Imaging, 2015)

A unified Bayesian-based compensated magnetic resonance imaging. - Ameneh Boroomand; Edward Li; Mohammad Javad Shafiee; Masoom A. Haider; Farzad Khalvati; Alexander Wong (EMBC, 2016)

Enhanced dual-stage correlated diffusion imaging. - Farzad Khalvati; Junjie Zhang 005; Masoom A. Haider; Alexander Wong (EMBC, 2016)

Bag of Bags: Nested Multi Instance Classification for Prostate Cancer Detection. - Farzad Khalvati; Junjie Zhang 005; Alexander Wong; Masoom A. Haider (ICMLA, 2016)

Sparse reconstruction of compressive sensing MRI using cross-domain stochastically fully connected conditional random fields. - Edward Li; Farzad Khalvati; Mohammad Javad Shafiee; Masoom A. Haider; Alexander Wong (BMC Medical Imaging, 2016)

Sequential Registration-Based Segmentation of the Prostate Gland in MR Image Volumes. - Farzad Khalvati; Aryan Salmanpour; Shahryar Rahnamayan; Masoom A. Haider; Hamid R. Tizhoosh (J. Digit. Imaging, 2016)

MAPS: A Quantitative Radiomics Approach for Prostate Cancer Detection. - Andrew Cameron; Farzad Khalvati; Masoom A. Haider; Alexander Wong (IEEE Trans. Biomed. Eng., 2016)

Noise-Compensated, Bias-Corrected Diffusion Weighted Endorectal Magnetic Resonance Imaging via a Stochastically Fully-Connected Joint Conditional Random Field Model. - Ameneh Boroomand; Mohammad Javad Shafiee; Farzad Khalvati; Masoom A. Haider; Alexander Wong (IEEE Trans. Medical Imaging, 2016)

A Machine Learning-Driven Approach to Computational Physiological Modeling of Skin Cancer. - Daniel S. Cho; Farzad Khalvati; David A. Clausi; Alexander Wong (ICIAR, 2017)

Fully Deep Convolutional Neural Networks for Segmentation of the Prostate Gland in Diffusion-Weighted MR Images. - Tyler Clark; Alexander Wong; Masoom A. Haider; Farzad Khalvati (ICIAR, 2017)

Discovery Radiomics via a Mixture of Deep ConvNet Sequencers for Multi-parametric MRI Prostate Cancer Classification. - Amir-Hossein Karimi; Audrey G. Chung; Mohammad Javad Shafiee; Farzad Khalvati; Masoom A. Haider; Ali Ghodsi 001; Alexander Wong (ICIAR, 2017)

Discovery Radiomics for Pathologically-Proven Computed Tomography Lung Cancer Prediction. - Devinder Kumar; Audrey G. Chung; Mohammad Javad Shafiee; Farzad Khalvati; Masoom A. Haider; Alexander Wong (ICIAR, 2017)

Segmentation of Prostate in Diffusion MR Images via Clustering. - Junjie Zhang 005; Sameer Baig; Alexander Wong; Masoom A. Haider; Farzad Khalvati (ICIAR, 2017)

CT texture features are associated with overall survival in pancreatic ductal adenocarcinoma - a quantitative analysis. - Armin Eilaghi; Sameer Baig; Yucheng Zhang; Junjie Zhang 005; Paul Karanicolas; Steven Gallinger; Farzad Khalvati; Masoom A. Haider (BMC Medical Imaging, 2017)

Discovery Radiomics via Evolutionary Deep Radiomic Sequencer Discovery for Pathologically-Proven Lung Cancer Detection. - Mohammad Javad Shafiee; Audrey G. Chung; Farzad Khalvati; Masoom A. Haider; Alexander Wong (CoRR, 2017)

MPCaD: a multi-scale radiomics-driven framework for automated prostate cancer localization and detection. - Farzad Khalvati; Junjie Zhang 005; Audrey G. Chung; Mohammad Javad Shafiee; Alexander Wong; Masoom A. Haider (BMC Medical Imaging, 2018)

ProstateGAN: Mitigating Data Bias via Prostate Diffusion Imaging Synthesis with Generative Adversarial Networks. - Xiaodan Hu; Audrey G. Chung; Paul W. Fieguth; Farzad Khalvati; Masoom A. Haider; Alexander Wong (CoRR, 2018)

PI-RADS guided discovery radiomics for characterization of prostate lesions with diffusion-weighted MRI. - Farzad Khalvati; Yucheng Zhang; Phuong H. U. Le; Isha Gujrathi; Masoom A. Haider (Computer-Aided Diagnosis, 2019)

Improving Prognostic Value of CT Deep Radiomic Features in Pancreatic Ductal Adenocarcinoma Using Transfer Learning. - Yucheng Zhang; Edrise M. Lobo-Mueller; Paul Karanicolas; Steven Gallinger; Masoom A. Haider; Farzad Khalvati (CoRR, 2019)

Prostate Cancer Detection using Deep Convolutional Neural Networks. - Sunghwan Yoo; Isha Gujrathi; Masoom A. Haider; Farzad Khalvati (CoRR, 2019)

Improving Prognostic Performance in Resectable Pancreatic Ductal Adenocarcinoma using Radiomics and Deep Learning Features Fusion in CT Images. - Yucheng Zhang; Edrise M. Lobo-Mueller; Paul Karanicolas; Steven Gallinger; Masoom A. Haider; Farzad Khalvati (CoRR, 2019)

A Transfer Learning Approach for Automated Segmentation of Prostate Whole Gland and Transition Zone in Diffusion Weighted MRI. - Saman Motamed; Isha Gujrathi; Dominik Deniffel; Anton Oentoro; Masoom A. Haider; Farzad Khalvati (CoRR, 2019)

Evolution-based Fine-tuning of CNNs for Prostate Cancer Detection. - Khashayar Namdar; Isha Gujrathi; Masoom A. Haider; Farzad Khalvati (CoRR, 2019)

CNN-based survival model for pancreatic ductal adenocarcinoma in medical imaging. - Yucheng Zhang; Edrise M. Lobo-Mueller; Paul Karanicolas; Steven Gallinger; Masoom A. Haider; Farzad Khalvati (BMC Medical Imaging, 2020)

Inception Augmentation Generative Adversarial Network. - Saman Motamed; Farzad Khalvati (CoRR, 2020)

A Brief Review of Deep Multi-task Learning and Auxiliary Task Learning. - Partoo Vafaeikia; Khashayar Namdar; Farzad Khalvati (CoRR, 2020)

RANDGAN: Randomized Generative Adversarial Network for Detection of COVID-19 in Chest X-ray. - Saman Motamed; Patrik Rogalla; Farzad Khalvati (CoRR, 2020)

Prognostic Value of Transfer Learning Based Features in Resectable Pancreatic Ductal Adenocarcinoma. - Yucheng Zhang; Edrise M. Lobo-Mueller; Paul Karanicolas; Steven Gallinger; Masoom A. Haider; Farzad Khalvati (Frontiers Artif. Intell., 2020)

Radiomics Driven Diffusion Weighted Imaging Sensing Strategies for Zone-Level Prostate Cancer Sensing. - Chris Dulhanty; Linda Wang; Maria Cheng; Hayden Gunraj; Farzad Khalvati; Masoom A. Haider; Alexander Wong (Sensors, 2020)

Inception-GAN for Semi-supervised Detection of Pneumonia in Chest X-rays. - Saman Motamed; Farzad Khalvati (EMBC, 2021)

Multi-class Generative Adversarial Networks: Improving One-class Classification of Pneumonia Using Limited Labeled Data. - Saman Motamed; Farzad Khalvati (EMBC, 2021)

Multi-class Generative Adversarial Nets for Semi-supervised Image Classification. - Saman Motamed; Farzad Khalvati (CoRR, 2021)

Vanishing Twin GAN: How training a weak Generative Adversarial Network can improve semi-supervised image classification. - Saman Motamed; Farzad Khalvati (CoRR, 2021)

Localized Perturbations For Weakly-Supervised Segmentation of Glioma Brain Tumours. - Sajith Rajapaksa; Farzad Khalvati (CoRR, 2021)

Improving the Segmentation of Pediatric Low-Grade Gliomas through Multitask Learning. - Partoo Vafaeikia; Matthias W. Wagner; Uri Tabori; Birgit Ertl-Wagner; Farzad Khalvati (CoRR, 2021)

A Transfer Learning-Based Active Learning Framework for Brain Tumor Classification. - Ruqian Hao; Khashayar Namdar; Lin Liu; Farzad Khalvati (Frontiers Artif. Intell., 2021)

A Modified AUC for Training Convolutional Neural Networks: Taking Confidence Into Account. - Khashayar Namdar; Masoom A. Haider; Farzad Khalvati (Frontiers Artif. Intell., 2021)

A Comprehensive Study of Data Augmentation Strategies for Prostate Cancer Detection in Diffusion-Weighted MRI Using Convolutional Neural Networks. - Ruqian Hao; Khashayar Namdar; Lin Liu; Masoom A. Haider; Farzad Khalvati (J. Digit. Imaging, 2021)

Improving the Segmentation of Pediatric Low-Grade Gliomas Through Multitask Learning. - Partoo Vafaeikia; Matthias W. Wagner; Cynthia Hawkins; Uri Tabori; Birgit Ertl-Wagner; Farzad Khalvati (EMBC, 2022)

Exploring COVID-19 Related Stressors Using Topic Modeling. - Yue Tong Leung; Farzad Khalvati (CoRR, 2022)

Improving Disease Classification Performance and Explainability of Deep Learning Models in Radiology with Heatmap Generators. - Akino Watanabe; Sara Ketabi; Khashayar Namdar; Farzad Khalvati (CoRR, 2022)

Open-radiomics: A Research Protocol to Make Radiomics-based Machine Learning Pipelines Reproducible. - Ernest Namdar; Matthias W. Wagner; Birgit Ertl-Wagner; Farzad Khalvati (CoRR, 2022)

Using Multi-modal Data for Improving Generalizability and Explainability of Disease Classification in Radiology. - Pranav Agnihotri; Sara Ketabi; Khashayar Namdar; Farzad Khalvati (CoRR, 2022)

Minimizing the Effect of Noise and Limited Dataset Size in Image Classification Using Depth Estimation as an Auxiliary Task with Deep Multitask Learning. - Khashayar Namdar; Partoo Vafaeikia; Farzad Khalvati (CoRR, 2022)

Superpixel Generation and Clustering for Weakly Supervised Brain Tumor Segmentation in MR Images. - Jay J. Yoo; Khashayar Namdar; Farzad Khalvati (CoRR, 2022)

Introducing Vision Transformer for Alzheimer's Disease classification task with 3D input. - Zilun Zhang; Farzad Khalvati (CoRR, 2022)

Tumor-location-guided CNNs for Pediatric Low-grade Glioma Molecular Biomarker Classification Using MRI. - Khashayar Namdar; Matthias W. Wagner; Kareem Kudus; Cynthia Hawkins; Uri Tabori; Birgit Ertl-Wagner; Farzad Khalvati (CoRR, 2022)

Optimized Global Perturbation Attacks For Brain Tumour ROI Extraction From Binary Classification Models. - Sajith Rajapaksa; Farzad Khalvati (CoRR, 2022)

A novel GAN-based paradigm for weakly supervised brain tumor segmentation of MR images. - Jay J. Yoo; Khashayar Namdar; Matthias W. Wagner; Liana Nobre; Uri Tabori; Cynthia Hawkins; Birgit B. Ertl-Wagner; Farzad Khalvati (CoRR, 2022)

A Comprehensive Study of Radiomics-based Machine Learning for Fibrosis Detection. - Jay J. Yoo; Khashayar Namdar; Chris McIntosh; Farzad Khalvati; Patrik Rogalla (CoRR, 2022)

Using Large Text To Image Models with Structured Prompts for Skin Disease Identification: A Case Study. - Sajith Rajapaksa; Jean Marie Uwabeza Vianney; Renell Castro; Farzad Khalvati; Shubhra Aich (ICCV (Workshops), 2023)

Multimodal Learning for Improving Performance and Explainability of Chest X-Ray Classification. - Sara Ketabi; Pranav Agnihotri; Hamed Zakeri; Khashayar Namdar; Farzad Khalvati (ISIC/Care-AI/MedAGI/DeCaF@MICCAI, 2023)

Combining Weakly Supervised Segmentation with Multitask Learning for Improved 3D MRI Brain Tumour Classification. - Sajith Rajapaksa; Khashayar Namdar; Farzad Khalvati (MILLanD@MICCAI, 2023)

Evaluating Knowledge Transfer in the Neural Network for Medical Images. - Sina Akbarian; Laleh Seyyed-Kalantari; Farzad Khalvati; Elham Dolatabadi (IEEE Access, 2023)

Advanced Receiver Operating Characteristic Curve Analysis to Identify Outliers in Binary Machine Learning Classifications for Precision Medicine. - Khashayar Namdar; Farzad Khalvati (BHI, 2024)

Improving Interpretability of Radiology Report-based Pediatric Brain Tumor Pathology Classification and Key-phrases Extraction Using Large Language Models. - Chen Zhao; Kareem Kudus; Sara Ketabi; Khashayar Namdar; Matthias W. Wagner; Birgit B. Ertl-Wagner; Farzad Khalvati (BHI, 2024)

Edge-Enhanced Dilated Residual Attention Network for Multimodal Medical Image Fusion. - Meng Zhou; Yuxuan Zhang; Xiaolan Xu; Jiayi Wang; Farzad Khalvati (BIBM, 2024)

Anomaly Detection in Pediatric and Adults Brain MRI with Generative Model. - Chaojun Chen; Khashayar Namdar; Matthias W. Wagner; Birgit B. Ertl-Wagner; Farzad Khalvati (EMBC, 2024)

Automating Cobb Angle Measurement for Adolescent Idiopathic Scoliosis using Instance Segmentation. - Chaojun Chen; Khashayar Namdar; Yujie Wu; Shahob Hosseinpour; Manohar Shroff; Andrea Doria 001; Farzad Khalvati (EMBC, 2024)

Conditional Generation of 3D Brain Tumor Regions via VQGAN and Temporal-Agnostic Masked Transformer. - Meng Zhou; Farzad Khalvati (MIDL, 2024)

Deep superpixel generation and clustering for weakly supervised segmentation of brain tumors in MR images. - Jay J. Yoo; Khashayar Namdar; Farzad Khalvati (BMC Medical Imaging, 2024)

Improving Pediatric Low-Grade Neuroepithelial Tumors Molecular Subtype Identification Using a Novel AUROC Loss Function for Convolutional Neural Networks. - Khashayar Namdar; Matthias W. Wagner; Cynthia Hawkins; Uri Tabori; Birgit B. Ertl-Wagner; Farzad Khalvati (CoRR, 2024)

Opportunities for Persian Digital Humanities Research with Artificial Intelligence Language Models; Case Study: Forough Farrokhzad. - Arash Rasti-Meymandi; Zahra Hosseini; Sina Davari; Abolfazl Moshiri; Shabnam Rahimi-Golkhandan; Khashayar Namdar; Nikta Feizi; Mohamad Tavakoli-Targhi; Farzad Khalvati (CoRR, 2024)

Tumor Location-weighted MRI-Report Contrastive Learning: A Framework for Improving the Explainability of Pediatric Brain Tumor Diagnosis. - Sara Ketabi; Matthias W. Wagner; Cynthia Hawkins; Uri Tabori; Birgit Betina Ertl-Wagner; Farzad Khalvati (CoRR, 2024)

Generating 3D brain tumor regions in MRI using vector-quantization Generative Adversarial Networks. - Meng Zhou; Matthias W. Wagner; Uri Tabori; Cynthia Hawkins; Birgit B. Ertl-Wagner; Farzad Khalvati (Comput. Biol. Medicine, 2025)

AI-Driven MRI-based Brain Tumour Segmentation Benchmarking. - Connor Ludwig; Khashayar Namdar; Farzad Khalvati (CoRR, 2025)

Non-invasive liver fibrosis screening on CT images using radiomics. - Jay J. Yoo; Khashayar Namdar; Sean Carey; Sandra E. Fischer; Chris McIntosh; Farzad Khalvati; Patrik Rogalla (BMC Medical Imaging, 2025)