1. Saeed Izadi. Deep Learning for Medical Image Restoration. Doctoral Thesis, School of Computing Science, Faculty of Applied Sciences, Simon Fraser University, June 2022. [bibtex-key = phd2022izadi]

1. Saeed Izadi, Isaac Shiri, Carlos Uribe, Parham Geramifar, Habib Zaidi, Arman Rahmim, and Ghassan Hamarneh. Enhanced Direct Joint Attenuation and Scatter Correction of Whole-Body PET Images via Context-Aware Deep Networks. Zeitschrift fuer Medizinische Physik, 000(000):000-000, 2024. Keyword(s): Enhancement/Restoration/Denoising, Deep Learning, Functional/Molecular/Dynamic Imaging. [bibtex-key = zmedphys2024]



2. Ben Cardoen, Kurt Vandevoorde, Guang Gao, Milene Ortiz-Silva, Parsa Alan, Ellie Tiliakou, William Liu, A. Wayne Vogl, Ghassan Hamarneh, and Ivan Robert Nabi. Membrane contact site detection (MCS-DETECT) reveals dual control of rough mitochondria-ER contacts (Cardoen, Vandevoorde, Gao, and Ortiz: Joint first authors; Hamarneh and Nabi: Joint senior authors). The Journal Of Cell Biology (JCB), 1(jcb.202206109):000-000, 11 2023. Keyword(s): Super Resolution Microscopy, Object Detection, Restoration, Reconstruction, Interaction. [bibtex-key = jcb2023]



3. Saeed Izadi, Darren Sutton, and Ghassan Hamarneh. Image Denoising in the Deep Learning Era. Artificial Intelligence Review, 000(000):1-46, 2022. Keyword(s): Enhancement/Restoration/Denoising, Machine Learning, Deep Learning, Survey/Review. [bibtex-key = aire2022]

1. Ben Cardoen, Kurt Vandevoorde, Guang Gao, Milene Ortiz-Silva, Parsa Alan, Ellie Tiliakou, William Liu, A. Wayne Vogl, Ghassan Hamarneh, and Ivan Robert Nabi. Membrane contact site detection (MCS-DETECT) reveals dual control of rough mitochondria–ER contacts (Cardoen, Vandevoorde, Gao, and Ortiz: Joint first authors; Hamarneh and Nabi: Joint senior authors). In Keystone Symposia on Molecular and Cellular Biology - Organelle Membrane Contact Sites in Health and Disease (Joint with: Mitochondria Signaling and Disease), pages 1, 2024. Keyword(s): Super Resolution Microscopy, Object Detection, Restoration, Reconstruction, Interaction. [bibtex-key = ksmcb2024a]



2. Tanya Gatsak, Kumar Abhishek, Hanene Ben Yedder, Saeid Asgari Taghanaki, and Ghassan Hamarneh. PET-Disentangler: PET Lesion Segmentation via Disentangled Healthy and Disease Feature Representations. In The Society of Nuclear Medicine and Molecular Imaging (SNMMI) Annual Meeting, pages 1, 2024. Keyword(s): Enhancement/Restoration/Denoising, Deep Learning, Functional/Molecular/Dynamic Imaging, Segmentation. [bibtex-key = snmmi2024]



3. Saeed Izadi, Isaac Shiri, Carlos Uribe, Parham Geramifar, Habib Zaidi, Arman Rahmim, and Ghassan Hamarneh. Context-Aware Filtering for Direct Joint Attenuation and Scatter Correction of Whole-Body PET Images. In The Society of Nuclear Medicine and Molecular Imaging (SNMMI) Annual Meeting, pages 1, 2022. Keyword(s): Enhancement/Restoration/Denoising, Deep Learning, Functional/Molecular/Dynamic Imaging. [bibtex-key = snmmi2022]



4. Saeed Izadi and Ghassan Hamarneh. Patch-based Non-Local Bayesian Networks for Blind Confocal Microscopy Denoising. In Lecture Notes in Computer Science, Medical Image Computing and Computer-Assisted Intervention (MICCAI), volume 12265, pages 46–55, 2020. Keyword(s): Microscopy, Enhancement/Restoration/Denoising, Machine Learning, Deep Learning. [bibtex-key = miccai2020]



5. Saeed Izadi, Zahra Mirikharaji, Mengliu Zhao, and Ghassan Hamarneh. WhiteNNer - Blind Image Denoising via Noise Whiteness Priors. In International Conference on Computer Vision workshop on Visual Recognition for Medical Images (ICCV VRMI), pages 476-484, 2019. Keyword(s): Microscopy, Enhancement/Restoration/Denoising, Machine Learning, Deep Learning. [bibtex-key = iccv_vrmi2019b]



6. Saeed Izadi, Darren Sutton, and Ghassan Hamarneh. Image Super Resolution via Bilinear Pooling: Application to Confocal Endomicroscopy. In Medical Image Computing and Computer-Assisted Intervention Workshop on Machine Learning for Medical Image Reconstruction (MICCAI MLMIR), volume 11905, pages 236-244, 2019. Keyword(s): Microscopy, Super Resolution, Enhancement/Restoration/Denoising, Machine Learning, Deep Learning. [bibtex-key = miccai_mlmir2019]



7. Saeed Izadi, Kathleen Moriarty, and Ghassan Hamarneh. Can Deep Learning Relax Endomicroscopy Hardware Miniaturization Requirements?. In Lecture Notes in Computer Science, Medical Image Computing and Computer-Assisted Intervention (MICCAI), volume 11070, pages 57-64, 2018. Keyword(s): Microscopy, Super Resolution, Enhancement/Restoration/Denoising, Machine Learning, Deep Learning. [bibtex-key = miccai2018c]

1. Saeed Izadi, Isaac Shiri, Carlos Uribe, Parham Geramifar, Habib Zaidi, Arman Rahmim, and Ghassan Hamarneh. Enhanced Direct Joint Attenuation and Scatter Correction of Whole-Body PET Images via Context-Aware Deep Networks. Technical report medRxiv 2022.05.26.22275662, May 2022. Keyword(s): Enhancement/Restoration/Denoising, Deep Learning, Functional/Molecular/Dynamic Imaging. [bibtex-key = medrxiv2022_20220526]



2. Saeed Izadi, Darren Sutton, and Ghassan Hamarneh. Image Denoising in the Deep Learning Era. Technical report Research Square (Preprint) 1806416, 6 2022. Keyword(s): Deep Learning, Enhancement/Restoration/Denoising, Survey/Review. [bibtex-key = research_square2022_1806416]



3. Saeed Izadi and Ghassan Hamarneh. Patch-based Non-Local Bayesian Networks for Blind Confocal Microscopy Denoising. Technical report arxiv:2003.11177, 3 2020. Keyword(s): Microscopy, Enhancement/Restoration/Denoising, Machine Learning, Deep Learning. [bibtex-key = arxiv:2003.11177]



4. Saeed Izadi, Darren Sutton, and Ghassan Hamarneh. Image Super Resolution via Bilinear Pooling: Application to Confocal Endomicroscopy. Technical report arxiv:1906.07802, 6 2019. Keyword(s): Microscopy, Super Resolution, Enhancement/Restoration/Denoising, Machine Learning, Deep Learning. [bibtex-key = arxiv:1906.07802]

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All person copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

This document was translated from BibT_EX by bibtex2html