1. Mohammadsadegh Saberian. DEEMD: Drug Efficacy Estimation Against SARS-CoV-2 Based On Cell Morphology With Deep Multiple Instance Learning. Master's Thesis, School of Computing Science, Faculty of Applied Sciences, Simon Fraser University, April 2021.

1. Kumar Abhishek, Jeremy Kawahara, and Ghassan Hamarneh. Predicting the Clinical Management of Skin Lesions using Deep Learning. Nature - Scientific Reports, 11(7769):1-14, 2021. Keyword(s): Dermatology, Machine Learning, Deep Learning, Clinical Management.



2. Arafat Hussain, Ghassan Hamarneh, and Rafeef Garbi. Cascaded Localization Regression Neural Nets for Kidney Localization and Segmentation-free Volume Estimation. IEEE Transactions on Medical Imaging (IEEE TMI), 40(6):1555-1567, 2021. Keyword(s): Machine Learning, Deep Learning, Segmentation, Localization.



3. Arafat Hussain, Ghassan Hamarneh, and Rafeef Garbi. Learnable Image Histograms-based Deep Radiomics for Renal Cell Carcinoma Grading and Staging. Computerized Medical Imaging and Graphics (CMIG), 90(101924):1-10, 2021. Keyword(s): Classification, Machine Learning, Deep Learning.



4. Saeed Izadi and Ghassan Hamarneh. AECNN: Adversarial and Enhanced Convolutional Neural Networks (Chapter 7). Computer-Aided Analysis of Gastrointestinal Videos, pp 59-62, 2021. ISBN: 978-3-030-64339-3. Keyword(s): Segmentation, Deep Learning, Generative Adversarial Network, Microscopy.



5. Ali Majd, Mohammed AlJasser, Hengameh Mirzaalian, Jerry Shapiro, Ghassan Hamarneh, Harvey Lui, Leopoldo Duailibe Nogueira Santos, Thomas Chu, and Tim K. Lee. A novel automated approach to rapid and precise in vivo measurement of hair morphometrics using a smartphone. Skin Research and Technology (SRT), 27:1128–1134, 2021. Keyword(s): Anatomical Trees and Tubular Structures, Dermatology, Color/Multichannel/Vector-valued, Software and Tools.



6. Mohammad Momeny, Ali Asghar Neshat, Arafat Hussain, Solmaz Kia, Mahmoud Marhamati, Ahmad Jahanbakhshi, and Ghassan Hamarneh. Learning-to-Augment Strategy using Noisy and Denoised Data: Improving Generalizability of Deep CNN for the Detection of COVID-19 in X-ray Images. Computers in Biology and Medicine (CIBM), 136:104704, 2021. Keyword(s): Deep Learning, Classification, Augmentation, COVID19, SARS-CoV-2.



7. Saeid Asgari Taghanaki, Kumar Abhishek, Joseph Paul Cohen, Julien Cohen-Adad, and Ghassan Hamarneh. Deep Semantic Segmentation of Natural and Medical Images: A Review (Taghanaki and Abhishek: Joint first authors). Artificial Intelligence Review, 54(1):137-178, 2021. Keyword(s): Segmentation, Survey/Review, Machine Learning, Deep Learning.



8. Timothy H. Wong, Ismail M. Khater, Bharat Joshi, Mona Shahsavari, Ghassan Hamarneh, and Ivan Robert Nabi. Single molecule network analysis identifies structural changes to caveolae and scaffolds due to mutation of the caveolin-1 scaffolding domain (Wong and Khater: Joint first authors; Hamarneh and Nabi: Joint senior authors). Nature - Scientific Reports, 11(7810):1-14, 2021. Keyword(s): Super Resolution Microscopy, Single Molecule Localization Microscopy, Machine Learning.



9. Hanene Ben Yedder, Ben Cardoen, and Ghassan Hamarneh. Deep Learning for Biomedical Image Reconstruction: A Survey. Artificial Intelligence Review, 54(1):215-251, 2021. Keyword(s): Image Reconstruction, Machine Learning, Deep Learning.



10. Hanene Ben Yedder, Ben Cardoen, Majid Shokoufi, Farid Golnaraghi, and Ghassan Hamarneh. Multitask Deep Learning Reconstruction and Localization of Lesions in Limited Angle Diffuse Optical Tomography. IEEE Transactions on Medical Imaging (IEEE TMI), 41(3):515-530, 2021. Keyword(s): Image Reconstruction, Machine Learning, Deep Learning, Synthesis/Simulation/Augmentation.

1. Kumar Abhishek and Ghassan Hamarneh. Matthews Correlation Coefficient Loss for Deep Convolutional Networks: Application to Skin Lesion Segmentation. In IEEE International Symposium on Biomedical Imaging (IEEE ISBI), pages 225-229, 2021. Keyword(s): Segmentation, Machine Learning, Deep Learning, Dermatology, Optimization.



2. Kumar Abhishek, Jeremy Kawahara, and Ghassan Hamarneh. Direct AI-based Prediction of Clinical Management Bypassing Diagnosis: Application to Skin Lesions. In UBC Dermatology and Skin Science: Skin Research Day, 2021. Keyword(s): Deep Learning, Dermatology,.



3. Nourhan Bayasi, Ghassan Hamarneh, and Rafeef Garbi. Culprit-Prune-Net: Efficient Continual Sequential Multi-Domain Learning with Application to Skin Lesion Classification. In Lecture Notes in Computer Science, Medical Image Computing and Computer-Assisted Intervention (MICCAI), volume 12907, pages 165-175, 2021. Keyword(s): Classification, Dermatology, Machine Learning, Deep Learning, Continual Learning, Domain Generalization.



4. Ben Cardoen and Ghassan Hamarneh. Learning to look beyond what we can see: Leveraging statistical learning to improve scientific discovery from fluorescence microscopy. In Biomedical Imaging and Artificial Intelligence (BMIAI) cluster Fall Research Showcase, Vancouver, Canada, pages 1, 2021. Keyword(s): Super Resolution Microscopy, Single Molecule Localization Microscopy, Machine Learning, Deep Learning, Processing, Belief Theory.



5. Ben Cardoen, Timothy H. Wong, Parsa Alan, Sieun Lee, Joanne Aiko Matsubara, Ivan Robert Nabi, and Ghassan Hamarneh. Self-tuning Weakly Supervised Object Detection (SPECHT) of Sub-Diffraction Limited Caveolae and Scaffold and Amyloid-Beta Deposits. In American Society of Cell Biology -- Cell Bio 2021, 2021. Keyword(s): Object Detection, Super Resolution Microscopy, Belief Theory, Datasets.



6. Ben Cardoen, Timothy H. Wong, Ivan Robert Nabi, and Ghassan Hamarneh. Belief theory enables detection of Caveolae in superresolution microscopy.. In Microscopy Societies Symposium - Advanced Imaging and Analysis at Nanoscale, November 2021. Keyword(s): Object Detection, Super Resolution Microscopy, Belief Theory.



7. Weina Jin and Ghassan Hamarneh. Physician-Centered Explainable AI. In Biomedical Imaging and Artificial Intelligence (BMIAI) cluster Fall Research Showcase, Vancouver, Canada, pages 1, 2021. Keyword(s): Deep Learning, Explainable AI (XAI), Glioma Imaging.



8. Weina Jin, Xiaoxiao Li, and Ghassan Hamarneh. One Map Does Not Fit All: Evaluating Saliency Map Explanation on Multi-Modal Medical Images. In International Conference on Machine Learning (ICML) workshop on Interpretable Machine Learning in Healthcare (IMLH), pages 1-13, 2021. Keyword(s): Deep Learning, Explainable AI (XAI), Glioma Imaging, Multimodal.



9. Ismail M. Khater, Timothy H. Wong, Stéphane Vassilopoulos, Ivan Robert Nabi, and Ghassan Hamarneh. SuperResNET: a GUI software package for single molecule localization microscopy cluster analysis (Nabi and Hamarneh: Joint senior authors). In Single Molecule Localization Microscopy Symposium - Current Trends, pages 1, 2021. Keyword(s): Super Resolution Microscopy, Single Molecule Localization Microscopy, Software and Tools, Network Modelling and Analysis, Machine Learning.



10. Mia McLean, Lynne Williams, Colin J. Brown, Ghassan Hamarneh, Cecil Chau, Joanne Weinberg, Anne Synnes, Steven Miller, and Ruth Grunau. Neonatal Pain-related Stress, Neonatal Structural Brain Subnetworks, Cortisol and Behavior at 4 years in Children Born Very Preterm. In 54th Annual Meeting of the International Society for Developmental Psychobiology, Chicago, USA, pages 1, 2021. Keyword(s): Diffusion MRI/Tensor-valued, Neurodevelopment, Connectome, Machine Learning.



11. Mia McLean, Lynne Williams, Jeremy Kawahara, Colin J. Brown, Ghassan Hamarneh, Joanne Weinberg, Anne Synnes, Steven Miller, and Ruth Grunau. Associations Between Neonatal Pain-Related Stress, Neonatal Brain Structural Connectome, and Behavior at School Age in Children Born Very Preterm. In 6th Annual Research Day Brain, Behaviour and Development (BB&D), Vancouver, Canada, pages 1, 2021. Keyword(s): Diffusion MRI/Tensor-valued, Neurodevelopment, Connectome, Machine Learning.



12. Zahra Mirikharaji, Kumar Abhishek, Saeed Izadi, and Ghassan Hamarneh. D-LEMA: Deep Learning Ensembles from Multiple Annotations. In Biomedical Imaging and Artificial Intelligence (BMIAI) cluster Fall Research Showcase, Vancouver, Canada, pages 1, 2021. Keyword(s): Dermatology, Color/Multichannel/Vector-valued, Machine Learning, Deep Learning, Segmentation.



13. Zahra Mirikharaji, Kumar Abhishek, Saeed Izadi, and Ghassan Hamarneh. D-LEMA: Deep Learning Ensembles from Multiple Annotations - Application to Skin Lesion Segmentation. In IEEE Computer Vision and Pattern Recognition (IEEE CVPR) ISIC Skin Image Analysis Workshop (CVPR ISIC), pages 1837-1846, 2021. Keyword(s): Dermatology, Color/Multichannel/Vector-valued, Machine Learning, Deep Learning, Segmentation.



14. Mengliu Zhao, Jeremy Kawahara, Sajjad Shamanian, Kumar Abhishek, and Ghassan Hamarneh. Computerized Localization and Tracking of Pigmented Skin Lesions on 3D Whole Body Textured Skin Meshes (Zhao and Kawahara: Joint first authors). In UBC Dermatology and Skin Science: Skin Research Day, 2021. Keyword(s): Deep Learning, Tracking, Dermatology.

1. Parsa Alan, Bharat Joshi, Ben Cardoen, Kurt Vandevoorde, Guang Gao, Yahya Mohammadzadeh, Ghassan Hamarneh, and Ivan Robert Nabi. Gp78-mediated basal mitophagy promotes mitochondrial health and limits mitochondrial ROS production (Alan, Joshi, Cardoen, and Vandevoorde: Joint first authors; Hamarneh and Nabi: Joint senior authors). Technical report biorxiv:2021.09.17.460825, 9 2021. Keyword(s): Super Resolution Microscopy, Image Processing, Belief Theory.



2. Mengliu Zhao, Jeremy Kawahara, Sajjad Shamanian, Kumar Abhishek, Priyanka Chandrashekar, and Ghassan Hamarneh. Detection and Longitudinal Tracking of Pigmented Skin Lesions in 3D Total-Body Skin Textured Meshes (Zhao and Kawahara: Joint first authors). Technical report arXiv:2105.00374, 5 2021. Keyword(s): Dermatology, Machine Learning, Deep Learning, Optimization, Registration and Matching, Graph based, Tracking.

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