1. Aicha BenTaieb. Analyzing Cancers in Digitized Histopathology Images. Doctoral Thesis, School of Computing Science, Faculty of Applied Sciences, Simon Fraser University, September 2018. [bibtex-key = phd2018bentaieb]

1. Saeedeh Afshari, Aicha BenTaieb, and Ghassan Hamarneh. Automatic Localization of Normal Active Organs in 3D PET Scans. Computerized Medical Imaging and Graphics (CMIG), 70:111-118, 2018. Keyword(s): Deep Learning, Machine Learning, Functional/Molecular/Dynamic Imaging, Localization. [bibtex-key = cmig2018c]



2. Aicha BenTaieb and Ghassan Hamarneh. Adversarial Stain Transfer for Histopathology Image Analysis. IEEE Transactions on Medical Imaging (IEEE TMI), 37(3):792-802, 2018. Keyword(s): Color/Multichannel/Vector-valued, Machine Learning, Microscopy, Deep Learning, Generative Adversarial Network. [bibtex-key = tmi2018]



3. Aicha BenTaieb, Hector Li-Chang, David Huntsman, and Ghassan Hamarneh. A Structured Latent Model for Ovarian Carcinoma Subtyping from Histopathology Slides. Medical Image Analysis (MedIA), 39:194-205, 2017. Keyword(s): Color/Multichannel/Vector-valued, Machine Learning, Microscopy, Deep Learning, Datasets. [bibtex-key = media2017]



4. Aicha BenTaieb, Masoud Nosrati, Hector Li-Chang, David Huntsman, and Ghassan Hamarneh. Clinically-Inspired Automatic Classification of Ovarian Carcinoma Subtypes. Journal of Pathology Informatics, 7(1):1-28, 2016. Keyword(s): Color/Multichannel/Vector-valued, Machine Learning, Microscopy. [bibtex-key = jpi2016]

1. Saeedeh Afshari, Aicha BenTaieb, Zahra Mirikharaji, and Ghassan Hamarneh. Weakly Supervised Fully Convolutional Network for PET Lesion Segmentation. In SPIE Medical Imaging, volume 10949, pages 1-7, 2019. Keyword(s): Deep Learning, Machine Learning, Functional/Molecular/Dynamic Imaging, Localization. [bibtex-key = spiemi2019]



2. 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]



3. Aicha BenTaieb and Ghassan Hamarneh. Predicting Cancer with a Recurrent Visual Attention Model for Histopathology Images. In Lecture Notes in Computer Science, Medical Image Computing and Computer-Assisted Intervention (MICCAI), volume 11071, pages 129-137, 2018. Keyword(s): Color/Multichannel/Vector-valued, Machine Learning, Microscopy, Deep Learning. [bibtex-key = miccai2018b]



4. Hanene Ben Yedder, Aicha BenTaieb, Majid Shokoufi, Amir Zahiremami, Farid Golnaraghi, and Ghassan Hamarneh. Deep Learning based Image Reconstruction for Diffuse Optical Tomography. In Medical Image Computing and Computer-Assisted Intervention Workshop on Machine Learning for Medical Image Reconstruction (MICCAI MLMIR), volume 11074, pages 112-119, 2018. Keyword(s): Image Reconstruction, Diffuse Optical Tomography, Machine Learning, Deep Learning. [bibtex-key = miccai_mlmir2018]



5. Aicha BenTaieb and Ghassan Hamarneh. Artificial Pathologists: Machine Learning Models for Histopathology. In Annual SFU Health Research Day - Women's Health Research Symposium, 2017. Keyword(s): Color/Multichannel/Vector-valued, Machine Learning, Microscopy, Deep Learning. [bibtex-key = sfu_health2017]



6. Aicha BenTaieb and Ghassan Hamarneh. Topology Aware Fully Convolutional Networks For Histology Gland Segmentation. In 2nd Annual Health Technology Symposium, Vancouver, Canada, pages 1, 2017. Keyword(s): Color/Multichannel/Vector-valued, Machine Learning, Microscopy, Deep Learning. [bibtex-key = healthtech2017a]



7. Aicha BenTaieb and Ghassan Hamarneh. Uncertainty Driven Multi-Loss Fully Convolutional Networks for Histopathology. In Medical Image Computing and Computer-Assisted Intervention Workshop on Large-scale Annotation of Biomedical data and Expert Label Synthesis (MICCAI LABELS), volume 10552, pages 155-163, 2017. Keyword(s): Color/Multichannel/Vector-valued, Machine Learning, Microscopy, Deep Learning. [bibtex-key = miccai_labels2017a]



8. Aicha BenTaieb and Ghassan Hamarneh. Topology Aware Fully Convolutional Networks For Histology Gland Segmentation. In Lecture Notes in Computer Science, Medical Image Computing and Computer-Assisted Intervention (MICCAI), volume 9900, pages 460-468, 2016. Keyword(s): Color/Multichannel/Vector-valued, Machine Learning, Microscopy, Deep Learning. [bibtex-key = miccai2016a]



9. Aicha BenTaieb, Jeremy Kawahara, and Ghassan Hamarneh. Multi-Loss Convolutional Networks for Gland Analysis in Microscopy. In IEEE International Symposium on Biomedical Imaging (IEEE ISBI), pages 642-645, 2016. Keyword(s): Machine Learning, Microscopy, Deep Learning. [bibtex-key = isbi2016a]



10. Jeremy Kawahara, Aicha BenTaieb, and Ghassan Hamarneh. Deep Features to Classify Skin Lesions. In IEEE International Symposium on Biomedical Imaging (IEEE ISBI), pages 1397-1400, 2016. Keyword(s): Machine Learning, Dermatology, Deep Learning. [bibtex-key = isbi2016b]



11. Aicha BenTaieb, Hector Li-Chang, David Huntsman, and Ghassan Hamarneh. Automatic Diagnosis of Ovarian Carcinomas via Sparse Multiresolution Tissue Representation. In Lecture Notes in Computer Science, Medical Image Computing and Computer-Assisted Intervention (MICCAI), volume 9349, pages 629-636, 2015. Keyword(s): Machine Learning, Microscopy, Deep Learning. [bibtex-key = miccai2015b]

1. Aicha BenTaieb and Ghassan Hamarneh. Deep Learning Models for Digital Pathology. Technical report arxiv:1910.12329, 10 2019. Keyword(s): Color/Multichannel/Vector-valued, Machine Learning, Microscopy, Deep Learning, Generative Adversarial Network, Survey/Review. [bibtex-key = arxiv:1910.12329]



2. 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]

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