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2020 – today
- 2024
[i44]Khashayar Namdar, Matthias W. Wagner, Cynthia Hawkins, Uri Tabori, Birgit B. Ertl-Wagner, Farzad Khalvati:
Improving Pediatric Low-Grade Neuroepithelial Tumors Molecular Subtype Identification Using a Novel AUROC Loss Function for Convolutional Neural Networks. CoRR abs/2402.03547 (2024)- [i43]Arash Rasti-Meymandi, Zahra Hosseini, Sina Davari, Abolfazl Moshiri, Shabnam Rahimi-Golkhandan, Khashayar Namdar, Nikta Feizi, Mohamad Tavakoli-Targhi, Farzad Khalvati:
Opportunities for Persian Digital Humanities Research with Artificial Intelligence Language Models; Case Study: Forough Farrokhzad. CoRR abs/2405.06760 (2024) - 2023
- [j19]Sina Akbarian
, Laleh Seyyed-Kalantari, Farzad Khalvati, Elham Dolatabadi:
Evaluating Knowledge Transfer in the Neural Network for Medical Images. IEEE Access 11: 85812-85821 (2023) - [c26]Sajith Rajapaksa, Jean Marie Uwabeza Vianney, Renell Castro, Farzad Khalvati, Shubhra Aich:
Using Large Text To Image Models with Structured Prompts for Skin Disease Identification: A Case Study. ICCV (Workshops) 2023: 2686-2693 - [c25]Sara Ketabi, Pranav Agnihotri, Hamed Zakeri, Khashayar Namdar, Farzad Khalvati:
Multimodal Learning for Improving Performance and Explainability of Chest X-Ray Classification. ISIC/Care-AI/MedAGI/DeCaF@MICCAI 2023: 107-116 - [c24]Sajith Rajapaksa, Khashayar Namdar, Farzad Khalvati:
Combining Weakly Supervised Segmentation with Multitask Learning for Improved 3D MRI Brain Tumour Classification. MILLanD@MICCAI 2023: 171-180 - [i42]Sajith Rajapaksa, Jean Marie Uwabeza Vianney, Renell Castro, Farzad Khalvati, Shubhra Aich:
Using Large Text-to-Image Models with Structured Prompts for Skin Disease Identification: A Case Study. CoRR abs/2301.07178 (2023) - [i41]Meng Zhou, Matthias W. Wagner, Uri Tabori, Cynthia Hawkins, Birgit B. Ertl-Wagner, Farzad Khalvati:
Generating 3D Brain Tumor Regions in MRI using Vector-Quantization Generative Adversarial Networks. CoRR abs/2310.01251 (2023) - 2022
- [c23]Partoo Vafaeikia, Matthias W. Wagner, Cynthia Hawkins, Uri Tabori, Birgit Ertl-Wagner, Farzad Khalvati:
Improving the Segmentation of Pediatric Low-Grade Gliomas Through Multitask Learning. EMBC 2022: 2119-2122 - [i40]Yue Tong Leung, Farzad Khalvati:
Exploring COVID-19 Related Stressors Using Topic Modeling. CoRR abs/2202.00476 (2022) - [i39]Akino Watanabe, Sara Ketabi, Khashayar Namdar, Farzad Khalvati:
Improving Disease Classification Performance and Explainability of Deep Learning Models in Radiology with Heatmap Generators. CoRR abs/2207.00157 (2022) - [i38]Ernest Namdar, Matthias W. Wagner, Birgit Ertl-Wagner, Farzad Khalvati:
Open-radiomics: A Research Protocol to Make Radiomics-based Machine Learning Pipelines Reproducible. CoRR abs/2207.14776 (2022) - [i37]Pranav Agnihotri, Sara Ketabi, Khashayar Namdar, Farzad Khalvati:
Using Multi-modal Data for Improving Generalizability and Explainability of Disease Classification in Radiology. CoRR abs/2207.14781 (2022) - [i36]Khashayar Namdar, Partoo Vafaeikia, Farzad Khalvati:
Minimizing the Effect of Noise and Limited Dataset Size in Image Classification Using Depth Estimation as an Auxiliary Task with Deep Multitask Learning. CoRR abs/2208.10390 (2022) - [i35]Jay J. Yoo, Khashayar Namdar, Farzad Khalvati:
Superpixel Generation and Clustering for Weakly Supervised Brain Tumor Segmentation in MR Images. CoRR abs/2209.09930 (2022) - [i34]Zilun Zhang, Farzad Khalvati:
Introducing Vision Transformer for Alzheimer's Disease classification task with 3D input. CoRR abs/2210.01177 (2022) - [i33]Khashayar Namdar, Matthias W. Wagner, Kareem Kudus, Cynthia Hawkins, Uri Tabori, Birgit Ertl-Wagner, Farzad Khalvati:
Tumor-location-guided CNNs for Pediatric Low-grade Glioma Molecular Biomarker Classification Using MRI. CoRR abs/2210.07287 (2022) - [i32]Sajith Rajapaksa, Farzad Khalvati:
Optimized Global Perturbation Attacks For Brain Tumour ROI Extraction From Binary Classification Models. CoRR abs/2211.04926 (2022) - [i31]Jay J. Yoo, Khashayar Namdar, Matthias W. Wagner, Liana Nobre, Uri Tabori, Cynthia Hawkins, Birgit B. Ertl-Wagner, Farzad Khalvati:
A novel GAN-based paradigm for weakly supervised brain tumor segmentation of MR images. CoRR abs/2211.05269 (2022) - [i30]Chaojun Chen, Khashayar Namdar, Yujie Wu, Shahob Hosseinpour, Manohar Shroff, Andrea S. Doria, Farzad Khalvati:
Automating Cobb Angle Measurement for Adolescent Idiopathic Scoliosis using Instance Segmentation. CoRR abs/2211.14122 (2022) - [i29]Jay J. Yoo, Khashayar Namdar, Chris McIntosh, Farzad Khalvati, Patrik Rogalla:
A Comprehensive Study of Radiomics-based Machine Learning for Fibrosis Detection. CoRR abs/2211.14396 (2022) - 2021
- [j18]Khashayar Namdar, Masoom A. Haider, Farzad Khalvati:
A Modified AUC for Training Convolutional Neural Networks: Taking Confidence Into Account. Frontiers Artif. Intell. 4: 582928 (2021) - [j17]Ruqian Hao, Khashayar Namdar, Lin Liu, Farzad Khalvati:
A Transfer Learning-Based Active Learning Framework for Brain Tumor Classification. Frontiers Artif. Intell. 4: 635766 (2021) - [j16]Ruqian Hao, Khashayar Namdar, Lin Liu, Masoom A. Haider, Farzad Khalvati:
A Comprehensive Study of Data Augmentation Strategies for Prostate Cancer Detection in Diffusion-Weighted MRI Using Convolutional Neural Networks. J. Digit. Imaging 34(4): 862-876 (2021) - [c22]Saman Motamed, Farzad Khalvati:
Inception-GAN for Semi-supervised Detection of Pneumonia in Chest X-rays. EMBC 2021: 3774-3778 - [c21]Saman Motamed, Farzad Khalvati:
Multi-class Generative Adversarial Networks: Improving One-class Classification of Pneumonia Using Limited Labeled Data. EMBC 2021: 3817-3822 - [i28]Saman Motamed, Farzad Khalvati:
Multi-class Generative Adversarial Nets for Semi-supervised Image Classification. CoRR abs/2102.06944 (2021) - [i27]Saman Motamed, Farzad Khalvati:
Vanishing Twin GAN: How training a weak Generative Adversarial Network can improve semi-supervised image classification. CoRR abs/2103.02496 (2021) - [i26]Sajith Rajapaksa, Farzad Khalvati:
Localized Perturbations For Weakly-Supervised Segmentation of Glioma Brain Tumours. CoRR abs/2111.14953 (2021) - [i25]Partoo Vafaeikia, Matthias W. Wagner, Uri Tabori, Birgit Ertl-Wagner, Farzad Khalvati:
Improving the Segmentation of Pediatric Low-Grade Gliomas through Multitask Learning. CoRR abs/2111.14959 (2021) - 2020
- [j15]Yucheng Zhang, Edrise M. Lobo-Mueller, Paul Karanicolas, Steven Gallinger, Masoom A. Haider, Farzad Khalvati:
CNN-based survival model for pancreatic ductal adenocarcinoma in medical imaging. BMC Medical Imaging 20(1): 11 (2020) - [j14]Yucheng Zhang, Edrise M. Lobo-Mueller, Paul Karanicolas, Steven Gallinger, Masoom A. Haider, Farzad Khalvati:
Prognostic Value of Transfer Learning Based Features in Resectable Pancreatic Ductal Adenocarcinoma. Frontiers Artif. Intell. 3: 550890 (2020) - [j13]Chris Dulhanty, Linda Wang, Maria Cheng, Hayden Gunraj, Farzad Khalvati, Masoom A. Haider, Alexander Wong:
Radiomics Driven Diffusion Weighted Imaging Sensing Strategies for Zone-Level Prostate Cancer Sensing. Sensors 20(5): 1539 (2020) - [i24]Ruqian Hao, Khashayar Namdar, Lin Liu, Masoom A. Haider, Farzad Khalvati:
A Comprehensive Study of Data Augmentation Strategies for Prostate Cancer Detection in Diffusion-weighted MRI using Convolutional Neural Networks. CoRR abs/2006.01693 (2020) - [i23]Saman Motamed, Farzad Khalvati:
Inception Augmentation Generative Adversarial Network. CoRR abs/2006.03622 (2020) - [i22]Khashayar Namdar, Masoom A. Haider, Farzad Khalvati:
A Modified AUC for Training Convolutional Neural Networks: Taking Confidence into Account. CoRR abs/2006.04836 (2020) - [i21]Partoo Vafaeikia, Khashayar Namdar, Farzad Khalvati:
A Brief Review of Deep Multi-task Learning and Auxiliary Task Learning. CoRR abs/2007.01126 (2020) - [i20]Sina Akbarian, Laleh Seyyed-Kalantari, Farzad Khalvati, Elham Dolatabadi:
Evaluating Knowledge Transfer In Neural Network for Medical Images. CoRR abs/2008.13574 (2020) - [i19]Saman Motamed, Patrik Rogalla, Farzad Khalvati:
RANDGAN: Randomized Generative Adversarial Network for Detection of COVID-19 in Chest X-ray. CoRR abs/2010.06418 (2020) - [i18]Ruqian Hao, Khashayar Namdar, Lin Liu, Farzad Khalvati:
A Transfer Learning Based Active Learning Framework for Brain Tumor Classification. CoRR abs/2011.09265 (2020)
2010 – 2019
- 2019
- [c20]Farzad Khalvati, Yucheng Zhang, Phuong H. U. Le, Isha Gujrathi, Masoom A. Haider:
PI-RADS guided discovery radiomics for characterization of prostate lesions with diffusion-weighted MRI. Medical Imaging: Computer-Aided Diagnosis 2019: 1095042 - [i17]Yucheng Zhang, Edrise M. Lobo-Mueller, Paul Karanicolas, Steven Gallinger, Masoom A. Haider, Farzad Khalvati:
Improving Prognostic Value of CT Deep Radiomic Features in Pancreatic Ductal Adenocarcinoma Using Transfer Learning. CoRR abs/1905.09888 (2019) - [i16]Sunghwan Yoo, Isha Gujrathi, Masoom A. Haider, Farzad Khalvati:
Prostate Cancer Detection using Deep Convolutional Neural Networks. CoRR abs/1905.13145 (2019) - [i15]Yucheng Zhang, Edrise M. Lobo-Mueller, Paul Karanicolas, Steven Gallinger, Masoom A. Haider, Farzad Khalvati:
CNN-based Survival Model for Pancreatic Ductal Adenocarcinoma in Medical Imaging. CoRR abs/1906.10729 (2019) - [i14]Yucheng Zhang, Edrise M. Lobo-Mueller, Paul Karanicolas, Steven Gallinger, Masoom A. Haider, Farzad Khalvati:
Improving Prognostic Performance in Resectable Pancreatic Ductal Adenocarcinoma using Radiomics and Deep Learning Features Fusion in CT Images. CoRR abs/1907.04822 (2019) - [i13]Saman Motamed, Isha Gujrathi, Dominik Deniffel, Anton Oentoro, Masoom A. Haider, Farzad Khalvati:
A Transfer Learning Approach for Automated Segmentation of Prostate Whole Gland and Transition Zone in Diffusion Weighted MRI. CoRR abs/1909.09541 (2019) - [i12]Khashayar Namdar, Isha Gujrathi, Masoom A. Haider, Farzad Khalvati:
Evolution-based Fine-tuning of CNNs for Prostate Cancer Detection. CoRR abs/1911.01477 (2019) - 2018
- [j12]Farzad Khalvati, Junjie Zhang, Audrey G. Chung, Mohammad Javad Shafiee, Alexander Wong, Masoom A. Haider:
MPCaD: a multi-scale radiomics-driven framework for automated prostate cancer localization and detection. BMC Medical Imaging 18(1): 16:1-16:14 (2018) - [i11]Xiaodan Hu, Audrey G. Chung, Paul W. Fieguth, Farzad Khalvati, Masoom A. Haider, Alexander Wong:
ProstateGAN: Mitigating Data Bias via Prostate Diffusion Imaging Synthesis with Generative Adversarial Networks. CoRR abs/1811.05817 (2018) - 2017
- [j11]Armin Eilaghi, Sameer Baig, Yucheng Zhang, Junjie Zhang, Paul Karanicolas, Steven Gallinger, Farzad Khalvati, Masoom A. Haider:
CT texture features are associated with overall survival in pancreatic ductal adenocarcinoma - a quantitative analysis. BMC Medical Imaging 17(1): 38:1-38:7 (2017) - [c19]Amir-Hossein Karimi, Audrey G. Chung, Mohammad Javad Shafiee, Farzad Khalvati, Masoom A. Haider, Ali Ghodsi, Alexander Wong:
Discovery Radiomics via a Mixture of Deep ConvNet Sequencers for Multi-parametric MRI Prostate Cancer Classification. ICIAR 2017: 45-53 - [c18]Devinder Kumar, Audrey G. Chung, Mohammad Javad Shafiee, Farzad Khalvati, Masoom A. Haider, Alexander Wong:
Discovery Radiomics for Pathologically-Proven Computed Tomography Lung Cancer Prediction. ICIAR 2017: 54-62 - [c17]Daniel S. Cho, Farzad Khalvati, David A. Clausi, Alexander Wong:
A Machine Learning-Driven Approach to Computational Physiological Modeling of Skin Cancer. ICIAR 2017: 79-86 - [c16]Tyler Clark, Alexander Wong, Masoom A. Haider, Farzad Khalvati:
Fully Deep Convolutional Neural Networks for Segmentation of the Prostate Gland in Diffusion-Weighted MR Images. ICIAR 2017: 97-104 - [c15]Junjie Zhang, Sameer Baig, Alexander Wong, Masoom A. Haider, Farzad Khalvati:
Segmentation of Prostate in Diffusion MR Images via Clustering. ICIAR 2017: 471-478 - [i10]Mohammad Javad Shafiee, Audrey G. Chung, Farzad Khalvati, Masoom A. Haider, Alexander Wong:
Discovery Radiomics via Evolutionary Deep Radiomic Sequencer Discovery for Pathologically-Proven Lung Cancer Detection. CoRR abs/1705.03572 (2017) - 2016
- [j10]Edward Li, Farzad Khalvati, Mohammad Javad Shafiee, Masoom A. Haider, Alexander Wong:
Sparse reconstruction of compressive sensing MRI using cross-domain stochastically fully connected conditional random fields. BMC Medical Imaging 16: 51 (2016) - [j9]Farzad Khalvati, Aryan Salmanpour, Shahryar Rahnamayan, Masoom A. Haider, Hamid R. Tizhoosh:
Sequential Registration-Based Segmentation of the Prostate Gland in MR Image Volumes. J. Digit. Imaging 29(2): 254-263 (2016) - [j8]Andrew Cameron, Farzad Khalvati, Masoom A. Haider, Alexander Wong:
MAPS: A Quantitative Radiomics Approach for Prostate Cancer Detection. IEEE Trans. Biomed. Eng. 63(6): 1145-1156 (2016) - [j7]Ameneh Boroomand, Mohammad Javad Shafiee, Farzad Khalvati, Masoom A. Haider, Alexander Wong:
Noise-Compensated, Bias-Corrected Diffusion Weighted Endorectal Magnetic Resonance Imaging via a Stochastically Fully-Connected Joint Conditional Random Field Model. IEEE Trans. Medical Imaging 35(12): 2587-2597 (2016) - [c14]Ameneh Boroomand, Edward Li, Mohammad Javad Shafiee, Masoom A. Haider, Farzad Khalvati, Alexander Wong:
A unified Bayesian-based compensated magnetic resonance imaging. EMBC 2016: 1192-1195 - [c13]Farzad Khalvati, Junjie Zhang, Masoom A. Haider, Alexander Wong:
Enhanced dual-stage correlated diffusion imaging. EMBC 2016: 5537-5540 - [c12]Farzad Khalvati, Junjie Zhang, Alexander Wong, Masoom A. Haider:
Bag of Bags: Nested Multi Instance Classification for Prostate Cancer Detection. ICMLA 2016: 146-151 - 2015
- [j6]Audrey G. Chung, Farzad Khalvati, Mohammad Javad Shafiee, Masoom A. Haider, Alexander Wong:
Prostate Cancer Detection via a Quantitative Radiomics-Driven Conditional Random Field Framework. IEEE Access 3: 2531-2541 (2015) - [j5]Farzad Khalvati, Alexander Wong, Masoom A. Haider:
Automated prostate cancer detection via comprehensive multi-parametric magnetic resonance imaging texture feature models. BMC Medical Imaging 15: 27 (2015) - [j4]Farzad Khalvati, Mark D. Aagaard, Hamid R. Tizhoosh:
Window memoization: toward high-performance image processing software. J. Real Time Image Process. 10(1): 5-25 (2015) - [j3]Farzad Khalvati, Cristina Gallego-Ortiz, Sharmila Balasingham, Anne L. Martel:
Automated Segmentation of Breast in 3-D MR Images Using a Robust Atlas. IEEE Trans. Medical Imaging 34(1): 116-125 (2015) - [c11]Audrey G. Chung, Christian Scharfenberger, Farzad Khalvati, Alexander Wong, Masoom A. Haider:
Statistical Textural Distinctiveness in Multi-Parametric Prostate MRI for Suspicious Region Detection. ICIAR 2015: 368-376 - [c10]Ahmed A. Othman, Hamid R. Tizhoosh, Farzad Khalvati:
Self-Configuring and Evolving Fuzzy Image Thresholding. ICMLA 2015: 13-18 - [c9]Zehra Camlica, Hamid R. Tizhoosh, Farzad Khalvati:
Medical Image Classification via SVM Using LBP Features from Saliency-Based Folded Data. ICMLA 2015: 128-132 - [c8]Zehra Camlica, Hamid R. Tizhoosh, Farzad Khalvati:
Autoencoding the retrieval relevance of medical images. IPTA 2015: 550-555 - [c7]Alexander Wong, Farzad Khalvati, Masoom A. Haider:
Dual-stage correlated diffusion imaging. ISBI 2015: 75-78 - [c6]Shahid A. Haider, Mohammad Javad Shafiee, Audrey G. Chung, Farzad Khalvati, Anastasia Oikonomou, Alexander Wong, Masoom A. Haider:
Single-click, semi-automatic lung nodule contouring using hierarchical conditional random fields. ISBI 2015: 1139-1142 - [i9]Ahmed A. Othman, Hamid R. Tizhoosh, Farzad Khalvati:
Evolving Fuzzy Image Segmentation with Self-Configuration. CoRR abs/1504.06266 (2015) - [i8]Zehra Camlica, Hamid R. Tizhoosh, Farzad Khalvati:
Autoencoding the Retrieval Relevance of Medical Images. CoRR abs/1507.01251 (2015) - [i7]Audrey G. Chung, Mohammad Javad Shafiee, Devinder Kumar, Farzad Khalvati, Masoom A. Haider, Alexander Wong:
Discovery Radiomics for Multi-Parametric MRI Prostate Cancer Detection. CoRR abs/1509.00111 (2015) - [i6]Devinder Kumar, Mohammad Javad Shafiee, Audrey G. Chung, Farzad Khalvati, Masoom A. Haider, Alexander Wong:
Discovery Radiomics for Computed Tomography Cancer Detection. CoRR abs/1509.00117 (2015) - [i5]Zehra Camlica, Hamid R. Tizhoosh, Farzad Khalvati:
Medical Image Classification via SVM using LBP Features from Saliency-Based Folded Data. CoRR abs/1509.04619 (2015) - [i4]Ahmed A. Othman, Hamid R. Tizhoosh, Farzad Khalvati:
Self-Configuring and Evolving Fuzzy Image Thresholding. CoRR abs/1509.04664 (2015) - [i3]Mohammad Javad Shafiee, Audrey G. Chung, Devinder Kumar, Farzad Khalvati, Masoom A. Haider, Alexander Wong:
Discovery Radiomics via StochasticNet Sequencers for Cancer Detection. CoRR abs/1511.03361 (2015) - [i2]Ameneh Boroomand, Mohammad Javad Shafiee, Farzad Khalvati, Masoom A. Haider, Alexander Wong:
Noise-Compensated, Bias-Corrected Diffusion Weighted Endorectal Magnetic Resonance Imaging via a Stochastically Fully-Connected Joint Conditional Random Field Model. CoRR abs/1512.04636 (2015) - [i1]Edward Li, Farzad Khalvati, Mohammad Javad Shafiee, Masoom A. Haider, Alexander Wong:
Sparse Reconstruction of Compressive Sensing MRI using Cross-Domain Stochastically Fully Connected Conditional Random Fields. CoRR abs/1512.07947 (2015) - 2014
- [j2]Ahmed A. Othman, Hamid R. Tizhoosh, Farzad Khalvati:
EFIS - Evolving Fuzzy Image Segmentation. IEEE Trans. Fuzzy Syst. 22(1): 72-82 (2014) - [c5]Andrew Cameron, Amen Modhafar, Farzad Khalvati, Dorothy Lui, Mohammad Javad Shafiee, Alexander Wong, Masoom A. Haider:
Multiparametric MRI prostate cancer analysis via a hybrid morphological-textural model. EMBC 2014: 3357-3360 - 2011
- [c4]Farzad Khalvati, Mehdi Kianpour, Hamid R. Tizhoosh:
Cascaded Window Memoization for Medical Imaging. EANN/AIAI (2) 2011: 275-284 - 2010
- [j1]Farzad Khalvati, Mark D. Aagaard:
Window memoization: an efficient hardware architecture for high-performance image processing. J. Real Time Image Process. 5(3): 195-212 (2010)
2000 – 2009
- 2009
- [c3]Farzad Khalvati, Hamid R. Tizhoosh:
An efficient architecture for hardware implementations of image processing algorithms. CIIP 2009: 20-26 - [c2]Farzad Khalvati, Hamid R. Tizhoosh, Arsen R. Hajian:
Increasing Computational Redundancy of Digital Images via Multiresolutional Matching. ICIAR 2009: 146-157 - 2008
- [b1]Farzad Khalvati:
Computational Redundancy in Image Processing. University of Waterloo, Ontario, Canada, 2008 - 2004
- [c1]Mark D. Aagaard, Vlad C. Ciubotariu, Jason T. Higgins, Farzad Khalvati:
Combining Equivalence Verification and Completion Functions. FMCAD 2004: 98-112
Coauthor Index
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