1. Saeid Asgari Taghanaki. Improved Deep Semantic Medical Image Segmentation. Doctoral Thesis, School of Computing Science, Faculty of Applied Sciences, Simon Fraser University, November 2019. [bibtex-key = phd2019taghanaki]

1. 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. [bibtex-key = aire2020a]



2. Saeid Asgari Taghanaki, Yefeng Zheng, S. Kevin Zhou, Bogdan Georgescu, Puneet Sharma, Daguang Xu, Dorin Comaniciu, and Ghassan Hamarneh. Combo Loss: Handling Input and Output Imbalance in Multi-Organ Segmentation. Computerized Medical Imaging and Graphics (CMIG), 75:24-33, 2019. Keyword(s): Machine Learning, Deep Learning, Segmentation. [bibtex-key = cmig2019]



3. Saeid Asgari Taghanaki, Noirin Duggan, Hillgan Ma, Xinchi Hou, Anna Celler, Francois Benard, and Ghassan Hamarneh. Segmentation-Free Direct Tumor Volume and Metabolic Activity Estimation from PET Scans. Computerized Medical Imaging and Graphics (CMIG), 63(January):52-66, 2018. Keyword(s): Machine Learning, Segmentation, Functional/Molecular/Dynamic Imaging. [bibtex-key = cmig2018a]



4. Saeid Asgari Taghanaki, Jeremy Kawahara, Brandon Miles, and Ghassan Hamarneh. Pareto-Optimal Multi-objective Dimensionality Reduction Deep Auto-Encoder for Mammography Classification. Computer Methods and Programs in Biomedicine, 145:85-93, 2017. Keyword(s): Machine Learning, Deep Learning, Optimization. [bibtex-key = cmpb2017]



5. Saeid Asgari Taghanaki, Yonghuai Liu, Brandon Miles, and Ghassan Hamarneh. Geometry Based Pectoral Muscle Segmentation from MLO Mammogram Views. IEEE Transactions on Biomedical Engineering (IEEE TBME), 64(1):2662-2671, 2017. Keyword(s): Segmentation. [bibtex-key = tbme2017]

1. Amir Alimohammadi, Sauradip Nag, Saeid Asgari Taghanaki, Andrea Tagliasacchi, Ghassan Hamarneh, and Ali Mahdavi-Amiri. SMITE: Segment Me In TimE. In International Conference on Learning Representations (ICLR), 2025. Keyword(s): Deep Learning, Machine Learning, One-/Few-Shot Learning, Segmentation, Diffusion Models, Foundational Models, Spatio-Temporal. [bibtex-key = iclr2025]



2. Tanya Gatsak, Kumar Abhishek, Hanene Ben Yedder, Saeid Asgari Taghanaki, and Ghassan Hamarneh. Disentangled PET Lesion Segmentation. In IEEE International Symposium on Biomedical Imaging (IEEE ISBI), 2025. Keyword(s): Enhancement/Restoration/Denoising, Deep Learning, Functional/Molecular/Dynamic Imaging, Segmentation. [bibtex-key = isbi2025]



3. 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]



4. Aliasghar Khani, Saeid Asgari Taghanaki, Aditya Sanghi, Ali Mahdavi-Amiri, and Ghassan Hamarneh. SLiMe: Segment Like Me. In International Conference on Learning Representations (ICLR), 2024. Keyword(s): Deep Learning, Machine Learning, One-/Few-Shot Learning, Segmentation, Diffusion Models, Foundational Models. [bibtex-key = iclr2024]



5. Saeid Asgari Taghanaki, Aliasghar Khani, Fereshte Khani, Ali Gholami, Linh Tran, Ali Mahdavi-Amiri, and Ghassan Hamarneh. MaskTune: Mitigating Shortcut Learning by Tuning to Explore (Asgari, Khani, Khani, Gholami: Equal contribution). In Neural Information Processing Systems (NeurIPS), pages 1-13, 2022. Keyword(s): Classification, Deep Learning. [bibtex-key = neurips2022]



6. Saeid Asgari Taghanaki, Kumar Abhishek, Shekoofeh Azizi, and Ghassan Hamarneh. A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations. In IEEE Computer Vision and Pattern Recognition (IEEE CVPR), pages 11332-11341, 2019. Keyword(s): Machine Learning, Deep Learning, Segmentation, Classification. [bibtex-key = cvpr2019]



7. Saeid Asgari Taghanaki, Kumar Abhishek, and Ghassan Hamarneh. Improved Inference via Deep Input Transfer. In Lecture Notes in Computer Science, Medical Image Computing and Computer-Assisted Intervention (MICCAI), volume 11769, pages 819-827, 2019. Keyword(s): Segmentation, Machine Learning, Deep Learning. [bibtex-key = miccai2019b]



8. Saeid Asgari Taghanaki, Aicha BenTaieb, Anmol Sharma, S. Kevin Zhou, Yefeng Zheng, Bogdan Georgescu, Puneet Sharma, Daguang Xu, Dorin Comaniciu, and Ghassan Hamarneh. SAT: Select, Attend, and Transfer: Light, Learnable Skip Connections. In Medical Image Computing and Computer-Assisted Intervention Workshop on Machine Learning in Medical Imaging (MICCAI MLMI), volume 11861, pages 417-425, 2019. Keyword(s): Machine Learning, Deep Learning, Segmentation. [bibtex-key = miccai_mlmi2019b]



9. Saeid Asgari Taghanaki, Mohammad Havaei, Tess Berthier, Francis Dutil, Lisa Di Jorio, Ghassan Hamarneh, and Yoshua Bengio. InfoMask: Masked Variational Latent Representation to Localize Chest Disease. In Lecture Notes in Computer Science, Medical Image Computing and Computer-Assisted Intervention (MICCAI), volume 11769, pages 739-747, 2019. Keyword(s): Classification, Machine Learning, Deep Learning. [bibtex-key = miccai2019a]



10. Saeid Asgari Taghanaki, Arkadeep Das, and Ghassan Hamarneh. Vulnerability Analysis of Chest X-Ray Image Classification Against Adversarial Attacks. In Medical Image Computing and Computer-Assisted Intervention Workshop on Deep Learning Fails (MICCAI DLF), volume 11038, pages 87-94, 2018. Keyword(s): Machine Learning, Deep Learning, Adversarial Attacks. [bibtex-key = miccai_dlf2018]



11. Saeid Asgari Taghanaki, Noirin Duggan, Hillgan Ma, Anna Celler, Francois Benard, and Ghassan Hamarneh. Lesion volume Estimation from PET without Requiring Segmentation. In Quantitative Imaging Network (QIN) Annual Meeting, 2017. Keyword(s): Machine Learning, Segmentation, Functional/Molecular/Dynamic Imaging. [bibtex-key = qin2017]

1. Tanya Gatsak, Kumar Abhishek, Hanene Ben Yedder, Saeid Asgari Taghanaki, and Ghassan Hamarneh. Disentangled PET Lesion Segmentation. Technical report arxiv.2411.01758, 10 2024. Keyword(s): Enhancement/Restoration/Denoising, Deep Learning, Functional/Molecular/Dynamic Imaging, Segmentation. [bibtex-key = arxiv:2411.01758]



2. Aliasghar Khani, Saeid Asgari Taghanaki, Aditya Sanghi, Ali Mahdavi-Amiri, and Ghassan Hamarneh. SLiMe: Segment Like Me. Technical report arxiv.2309.03179, 9 2023. Keyword(s): Deep Learning, Segmentation. [bibtex-key = arxiv:2309.03179]



3. Saeid Asgari Taghanaki, Kumar Abhishek, Joseph Paul Cohen, Julien Cohen-Adad, and Ghassan Hamarneh. Deep Semantic Segmentation of Natural and Medical Images: A Review. Technical report arxiv:1910.07655, 10 2019. Keyword(s): Survey/Review, Segmentation, Machine Learning, Deep Learning. [bibtex-key = arxiv:1910.07655]



4. Saeid Asgari Taghanaki, Kumar Abhishek, and Ghassan Hamarneh. Improved Inference via Deep Input Transfer. Technical report arxiv:1904.02307, 4 2019. Keyword(s): Machine Learning, Deep Learning. [bibtex-key = arxiv:1904.02307]



5. Saeid Asgari Taghanaki, Kumar Abhishek, and Ghassan Hamarneh. Signed Input Regularization. Technical report arxiv:1911.07086, 12 2019. Keyword(s): Machine Learning, Deep Learning. [bibtex-key = arxiv:1911.07086]



6. Saeid Asgari Taghanaki, Mohammad Havaei, Tess Berthier, Francis Dutil, Lisa Di Jorio, Ghassan Hamarneh, and Yoshua Bengio. InfoMask: Masked Variational Latent Representation to Localize Chest Disease. Technical report arxiv:1903.11741, 3 2019. Keyword(s): Machine Learning, Deep Learning. [bibtex-key = arxiv:1903.11741]



7. Saeid Asgari Taghanaki, Aicha BenTaieb, Anmol Sharma, S. Kevin Zhou, Yefeng Zheng, Bogdan Georgescu, Puneet Sharma, Sasa Grbic, Zhoubing Xu, Dorin Comaniciu, and Ghassan Hamarneh. Select, Attend, and Transfer: Light, Learnable Skip Connections. Technical report arxiv:1703.04559, 4 2018. Keyword(s): Machine Learning, Deep Learning, Segmentation. [bibtex-key = arxiv:1804.05181]



8. Saeid Asgari Taghanaki, Yefeng Zheng, S. Kevin Zhou, Bogdan Georgescu, Puneet Sharma, Daguang Xu, Dorin Comaniciu, and Ghassan Hamarneh. Combo Loss: Handling Input and Output Imbalance in Multi-Organ Segmentation. Technical report arxiv:1703.04559, 5 2018. Keyword(s): Machine Learning, Deep Learning, Segmentation. [bibtex-key = arxiv:1805.02798]

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