Shahira Abousamra

PhD Student
Department of Computer Science
Stony Brook University

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Google Scholar
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About

I am a PhD student at Stony Brook University. I am advised by Dr. Chao Chen and Dr. Dimitris Samaras. My research is in computer vision, topological data analysis, and biomedical image analysis. I am specially interested in the intersection among all three. General computer vision solutions often do not work right out of the box when applied on biomedical images, making it essential to research solutions that target this domain. There are inherent spatial and topological features in biomedical images that often go overlooked. I am excited about researching solutions that take advantage of these various features.

Projects and Publications


Topology-Guided Multi Class Cell Context Generation for Digital Pathology.
S. Abousamra, R. Gupta, T. Kurc, D. Samaras, J. Saltz, C. Chen
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
[paper][poster][video][slides][CVPR Daily article]



Multi-Class Cell Detection Using Spatial Context Representation.
S. Abousamra, D. Belinsky, J. Arnam, F. Allard, E. Yee, R. Gupta, T. Kurc, D. Samaras, J. Saltz, C. Chen
International Conference on Computer Vision (ICCV), 2021, (Oral).
[paper][summary][video][code]



Localization in the Crowd with Topological Constraints.
S. Abousamra, M. Hoai, D. Samaras, C. Chen
AAAI Conference on Artificial Intelligence (AAAI), 2021.
Best presentation in domain award - SBU Computer Science Graduate Research Day, 2021
[paper][poster][video][code]


Unsupervised Stain Decomposition via Inversion Regulation for Multiplex Immunohistochemistry Images.
S. Abousamra*, D. Fassler, J. Yao, R. Gupta, T. Kurc, L. Escobar-Hoyos, D. Samaras, K. Shroyer, J. Saltz, C. Chen
Medical Imaging with Deep Learning (MIDL), 2023 (Oral).
[paper][code]

Deep learning-based image analysis methods for brightfield-acquired multiplex immunohistochemistry images.
D. Fassler*, S. Abousamra*, R. Gupta, C. Chen, M. Zhao, D. Paredes, S. Batool, B. Knudsen, L. Escobar-Hoyos, K. Shroyer, D. Samaras, T. Kurc, J. Saltz
Diagnostic Pathology, 2020.
[paper][code]

Weakly-Supervised Deep Stain Decomposition For Multiplex IHC Images.
S. Abousamra, D. Fassler, L. Hou, Y. Zhang, R. Gupta, T. Kurc, L. F. Escobar-Hoyos, D. Samaras, B. Knudson, K. Shroyer, J. Saltz, C. Chen
IEEE International Symposium on Biomedical Imaging (ISBI), 2020.
[paper][video][code]



Utilizing Automated Breast Cancer Detection to Identify Spatial Distributions of Tumor-infiltrating Lymphocytes in Invasive Breast Cancer.
H. Le, R. Gupta, L. Hou, S. Abousamra, D. Fassler, L. Torre-Healy, R. Moffitt, T. Kurc, D. Samaras, R. Batiste, T. Zhao, A. Rao, A. Van Dyke, A. Sharma, E. Bremer, J. Almeida, J. Saltz
The American journal of pathology, 2020.
[paper]

Learning from Thresholds: Fully Automated Classification of Tumor Infiltrating Lymphocytes for Multiple Cancer Types.
S. Abousamra, L. Hou, R. Gupta, C. Chen, D. Samaras, T. Kurc, R. Batiste, T. Zhao, S. Kenneth, J. Saltz
Computing Research Repository (CoRR), 2019.
[paper][code]



Localization and Tracking in 4D Fluorescence Microscopy Imagery.
S. Abousamra, S. Adar, N. Elia, R. Shilkrot
Computer Vision and Pattern Recognition Workshops (CVPRW), 2018.
Best poster award - Center of Excellence in Wireless and Information Technology (CEWIT) Conference, 2017
[paper][poster]