1. Kumar Abhishek. Input Space Augmentation For Skin Lesion Segmentation In Dermoscopic Images. Master's Thesis, School of Computing Science, Faculty of Applied Sciences, Simon Fraser University, April 2020.



2. Yiqi Yan. Attention-based Skin Lesion Recognition. Master's Thesis, School of Computing Science, Faculty of Applied Sciences, Simon Fraser University, April 2020.



3. Mengliu Zhao. Encoding Anatomical Tree Priors for Tubular Structure Extraction for Medical Images Analysis. Doctoral Thesis, School of Computing Science, Faculty of Applied Sciences, Simon Fraser University, April 2020.

1. Ali Arab, Betty Chinda, George Medvedev, William Siu, Tao Gu, Hui Guo, Sylvain Moreno, Ghassan Hamarneh, Martin Ester, and Xiaowei Song. A Fast and Fully-Automated Deep-Learning Approach for Accurate Haemorrhage Segmentation and Volume Quantification in Non-Contrast Whole-Head CT (Arabi and Chinda: Joint first authors). Nature - Scientific reports, 10(19389):1-12, 2020. Keyword(s): Deep Learning, Segmentation.



2. Ben Cardoen, Hanene Ben Yedder, Anmol Sharma, Keng C. Chou, Ivan Robert Nabi, and Ghassan Hamarneh. ERGO: Efficient Recurrent Graph Optimized Emitter Density Estimation in Single Molecule Localization Microscopy. IEEE Transactions on Medical Imaging (IEEE TMI), 39(6):1942-1956, 2020. Keyword(s): Super Resolution Microscopy, Single Molecule Localization Microscopy, Machine Learning.



3. Saurabh Garg, Ghassan Hamarneh, Allard Jongman, Joan Sereno, and Yue Wang. ADFAC: Automatic Detection of Facial Articulatory Features. MethodX, 7:101006, 2020. Keyword(s): Segmentation, Tracking, Color/Multichannel/Vector-valued, Speech and Language, Facial Analysis, Spatio-Temporal, Software and Tools.



4. Saurabh Garg, Lisa Y. W. Tang, Ghassan Hamarneh, Allard Jongman, Joan Sereno, and Yue Wang. Different facial cues for different speech styles in Mandarin tone articulation. The Journal of the Acoustical Society of America (JASA). Also appears in ASA Meeting, 148(4):2764-2764, 2020. Keyword(s): Tracking, Machine Learning, Color/Multichannel/Vector-valued, Speech and Language, Facial Analysis, Spatio-Temporal.



5. Weina Jin, Mostafa Fatehi, Kumar Abhishek, Mayur Mallya, Brian Toyota, and Ghassan Hamarneh. Artificial Intelligence in Glioma Imaging: Challenges and Advances. Journal of Neural Engineering, 17(2):021002, 2020. Keyword(s): Glioma Imaging, Machine Learning, Deep Learning, Survey/Review.



6. Ismail M. Khater, Ivan Robert Nabi, and Ghassan Hamarneh. A Review of Super-resolution Single Molecule Localization Microscopy Cluster Analysis and Quantification Methods. Cell Patterns, 1(3):2666-3899, 2020. Keyword(s): Super Resolution Microscopy, Single Molecule Localization Microscopy, Network Modelling and Analysis, Deep Learning, Machine Learning, Classification, Graph based, Biomarkers/Biosignatures, Survey/Review.



7. Chloe Lim, Hayyan Liaqat, William Siu, Ghassan Hamarneh, and George Medvedev. Future implementation of automated analysis tools for Multiple Sclerosis on conventional magnetic resonance imaging (Lim and Liaqat: Joint first authors; Hamarneh and Medvedev: Joint senior authors). Multiple Sclerosis. MSVirtual 2020 – Late Breaking News. Also appears in ACTRIMS-ECTRMS meeting, 1(3 SUPPL):99, 2020. Keyword(s): Segmentation, Software and Tools, Multiple Sclerosis, MRI.



8. Rory Long, Kathleen Moriarty, Ben Cardoen, Guang Gao, A. Wayne Vogl, François Jean, Ghassan Hamarneh, and Ivan Robert Nabi. Super Resolution Microscopy and Deep Learning Identify Zika Virus Reorganization of the Endoplasmic Reticulum (Long and Moriarty: Joint first authors; Hamarneh and Nabi: Joint senior authors). Nature - Scientific reports, 10(20937):1-18, 2020. Keyword(s): Super Resolution Microscopy, Single Molecule Localization Microscopy, Machine Learning, Deep Learning.



9. Brian Smith, John Buatti, Christian Bauer, Ethan Ulrich, Payam Ahmadvand, Mikalai Budzevich, Robert Gillies, Dmitry Goldgof, Milan Grkovski, Ghassan Hamarneh, Paul Kinahan, John Muzi, Mark Muzi, Charles Laymon, James Mountz, Sadek Nehmeh, Matthew Oborski, Binsheng Zhao, John Sunderland, and Reinhard Beichel. Multi-Site Technical and Clinical Performance Evaluation of Quantitative Imaging Biomarkers from 3D FDG PET Segmentations of Head and Neck Cancer Images. Tomography, 6(2):65-76, 2020. Keyword(s): Machine Learning, Segmentation, Functional/Molecular/Dynamic Imaging.

1. Kumar Abhishek, Ghassan Hamarneh, and Mark S. Drew. Illumination-based Transformations Improve Skin Lesion Segmentation in Dermoscopic Images. In IEEE Computer Vision and Pattern Recognition (IEEE CVPR) ISIC Skin Image Analysis Workshop (CVPR ISIC), pages 728-729, 2020. Keyword(s): Dermatology, Color/Multichannel/Vector-valued, Machine Learning, Deep Learning, Segmentation.



2. Ali Arab, Betty Chinda, William Siu, George Medvedev, Tao Gu, Hui Guo, Sylvain Moreno, Ghassan Hamarneh, Martin Ester, and Xiaowei Song. A fully-automated convolutional neural network with deep supervision approach for haemorrhage segmentation and volume quantification in CT scans. In American Society of Neuroradiology (ASNR), pages 1, 2020. Keyword(s): Deep Learning, Machine Learning, Segmentation.



3. Shahab Aslani, Vittorio Murino, Michael Dayan, Roger Tam, Diego Sona, and Ghassan Hamarneh. Scanner Invariant Multiple Sclerosis Lesion Segmentation from MRI. In IEEE International Symposium on Biomedical Imaging (IEEE ISBI), pages 781-785, 2020. Keyword(s): Segmentation, Machine Learning, Deep Learning, Multiple Sclerosis, MRI.



4. Ben Cardoen, Timothy H. Wong, Parsa Alan, Sieun Lee, Joanne Aiko Matsubara, Ivan Robert Nabi, and Ghassan Hamarneh. Automatic identification of protein complexes in multi-scale microscopy with applications tometastasis and Alzheimer disease. In The 2nd Annual Tri-Cluster Research Day, Canada, pages 1, 2020. Keyword(s): Super Resolution Microscopy, Single Molecule Localization Microscopy, Machine Learning, Processing, Belief Theory.



5. Ben Cardoen, Timothy H. Wong, Parsa Alan, Sieun Lee, Joanne Aiko Matsubara, Ivan Robert Nabi, and Ghassan Hamarneh. Belief theory enables identification of protein complexes in multi-scale microscopy with applications to metastasis and Alzheimer disease. In Centre for Artificial Intelligence Decision-making and Action (CAIDA), BC's AI Showcase, Canada, pages 1, 2020. Keyword(s): Super Resolution Microscopy, Single Molecule Localization Microscopy, Machine Learning, Processing, Belief Theory.



6. Saurabh Garg, Lisa Y. W. Tang, Ghassan Hamarneh, Allard Jongman, Joan Sereno, and Yue Wang. Different facial cues for different speech styles in Mandarin tone articulation. In Acoustical Society of America Meeting (ASA), pages 1, 2020. Keyword(s): Tracking, Machine Learning, Color/Multichannel/Vector-valued, Speech and Language, Facial Analysis, Spatio-Temporal.



7. 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.



8. Ismail M. Khater, Ivan Robert Nabi, and Ghassan Hamarneh. SuperNet: Super-resolution Network Analysis and Quantification of Single Molecule Clusters. In Single Molecule Localization Microscopy Symposium - Showtime, pages 1, 2020. Keyword(s): Super Resolution Microscopy, Single Molecule Localization Microscopy, Software and Tools, Network Modelling and Analysis, Machine Learning.



9. Chloe Lim, Hayyan Liaqat, William Siu, Ghassan Hamarneh, and George Medvedev. Future implementation of automated analysis tools for Multiple Sclerosis on conventional magnetic resonance imaging (Lim and Liaqat: Joint first authors; Hamarneh and Medvedev: Joint senior authors). In 8th joint Americas Committee for Treatment and Research in Multiple Sclerosis - European Committee for Treatment and Research in Multiple Sclerosis (joint ACTRIMS-ECTRMS), pages 1, 2020. Keyword(s): Segmentation, Software and Tools, Multiple Sclerosis, MRI.



10. M.Sadegh Saberian, Kathleen Moriarty, Andrea Olmstead, François Jean, Ivan Robert Nabi, Maxwell Libbrecht, and Ghassan Hamarneh. Drug Repurposing Efficacy Estimation based on Morphological Analysis of SARS-CoV-2 Infected Cells within a Multiple Instance Learning Framework. In Machine learning for computational biology conference (MLCB), pages 1-13, 2020. Keyword(s): Deep Learning, Machine Learning, COVID19, SARS-CoV-2.



11. Mengliu Zhao, Sajjad Shamanian, Priyanka Chandrashekar, Kumar Abhishek, Jeremy Kawahara, and Ghassan Hamarneh. Acquisition and Analysis of 3D Whole Body Skin Images for Dermatological Studies. In The 2nd Annual Tri-Cluster Research Day, Canada, pages 1, 2020. Keyword(s): Deep Learning, Dermatology.



12. Mengliu Zhao, Sajjad Shamanian, Priyanka Chandrashekar, Kumar Abhishek, Jeremy Kawahara, and Ghassan Hamarneh. Skin Lesion Localization and Tracking on 3D Whole Body Colored Surface Images. In Centre for Artificial Intelligence Decision-making and Action (CAIDA), BC's AI Showcase, Canada, pages 1, 2020. Keyword(s): Deep Learning, Dermatology.

1. Kumar Abhishek and Ghassan Hamarneh. Matthews Correlation Coefficient Loss for Deep Convolutional Networks: Application to Skin Lesion Segmentation. Technical report arXiv:2010.13454, 10 2020. Keyword(s): Dermatology, Machine Learning, Deep Learning, Segmentation.



2. Kumar Abhishek, Ghassan Hamarneh, and Mark S. Drew. Illumination-based Transformations Improve Skin Lesion Segmentation in Dermoscopic Images. Technical report arxiv:2003.10111, 3 2020. Keyword(s): Dermatology, Color/Multichannel/Vector-valued, Machine Learning, Deep Learning, Segmentation.



3. Kumar Abhishek, Jeremy Kawahara, and Ghassan Hamarneh. Predicting the Clinical Management of Skin Lesions Using Deep Learning. Technical report medRxiv 2020.11.02.20223941, November 2020. Keyword(s): Dermatology, Machine Learning, Deep Learning, Clinical Management.



4. Ben Cardoen and Ghassan Hamarneh. Introduction to Causality. Technical report SFU-Summit-20939, 12 2020. Keyword(s): Machine Learning, Deep Learning, Causality.



5. Ben Cardoen, Timothy H. Wong, Parsa Alan, Sieun Lee, Joanne Aiko Matsubara, Ivan Robert Nabi, and Ghassan Hamarneh. SPECHT: Self-tuning Plausibility Based Object Detection Enables Quantification of Conflict in Heterogeneous Multi-scale Microscopy (Nabi and Hamarneh: Joint senior authors). Technical report techrxiv:12971051, 9 2020. Keyword(s): Super Resolution Microscopy, Single Molecule Localization Microscopy, Machine Learning, Processing, Belief Theory, Object Detection, Datasets.



6. 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.



7. Ivan Klyuzhin, Yixi Xu, Anthony Ortiz, Juan Lavista Ferres, Ghassan Hamarneh, and Arman Rahmim. Testing the Ability of Convolutional Neural Networks to Learn Radiomic Features. Technical report medrxiv:20198077, September 2020. Keyword(s): Deep Learning, Machine Learning, Radiomics, Functional/Molecular/Dynamic Imaging.



8. Rory Long, Kathleen Moriarty, Ben Cardoen, Guang Gao, A. Wayne Vogl, François Jean, Ghassan Hamarneh, and Ivan Robert Nabi. Super Resolution Microscopy and Deep Learning Identify Zika Virus Reorganization of the Endoplasmic Reticulum (Long and Moriarty: Joint first authors; Hamarneh and Nabi: Joint senior authors. Technical report biorxiv:091611, 5 2020. Keyword(s): Super Resolution Microscopy, Single Molecule Localization Microscopy, Machine Learning, Deep Learning.



9. Zahra Mirikharaji, Kumar Abhishek, Saeed Izadi, and Ghassan Hamarneh. D-LEMA: Deep Learning Ensembles from Multiple Annotations - Application to Skin Lesion Segmentation. Technical report arXiv:2012.07206, 12 2020. Keyword(s): Dermatology, Machine Learning, Deep Learning, Segmentation.



10. Hanene Ben Yedder, Ben Cardoen, and Ghassan Hamarneh. Deep Learning for Biomedical Image Reconstruction: A Survey. Technical report arxiv:2002.12351, 2 2020. Keyword(s): Image Reconstruction, Machine Learning, Deep Learning, Survey/Review.



11. 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. Technical report techrxiv:13150805, 10 2020. Keyword(s): Image Reconstruction, Machine Learning, Deep Learning, Synthesis/Simulation/Augmentation, Diffuse Optical Tomography.

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