Recognition for Artificial Intelligence in Biomedical Imaging
Artificial intelligence designed to help scientists study the brain with greater precision earned a Best Poster Honorable Mention Award at the 16th Association for Computing Machinery Conference on Bioinformatics, Computational Biology, and Health Informatics. The conference brings together work in artificial intelligence for Bio-medicine from across computer science, statistics, biology, and clinical research.
The project was led by Sayed Mehedi Azim, a PhD candidate in the Computational and Integrative Biology Program, with collaborators Renuka Kumar, Brian Corbett, and Iman Dehzangi. Their poster, “From Pixels to Precision Neuroanatomy: Generative Artificial Intelligence for Automatic Segmentation and Identification of Hippocampal Regions,” presents a generative artificial intelligence approach for identifying regions of the hippocampus. The award recognizes the clarity of the team’s contribution and the direction of their ongoing work.
Azim also contributed to a second project titled “Toward Automated and Scalable Hematopoietic Stem Cell Sorting: A Deep Learning Approach,” which was shared during the conference’s Advances in Systems Immunology Workshop. Together, these presentations show how the team is applying artificial intelligence methods to questions in neuroanatomy and biomedical data analysis.
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Bridging Disciplines: The Center for Computational and Integrative Biology
The Center for Computational and Integrative Biology (CCIB) at Rutgers–Camden combines experimental and computational methods to address complex biological questions. CCIB offers graduate programs leading to M.S. and Ph.D. degrees, emphasizing a holistic understanding of biological systems from molecular to population levels. The curriculum equips students like Basirat with the skills to conduct innovative research at the intersection of biology, chemistry, computer science, mathematics, and physics.
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