Haibin Ling, a professor in the Department of Computer Science, is part of a team of researchers developing a new way to analyze breast cancer imaging. The team’s approach incorporates mathematical modeling and deep learning and will yield results that are easier to interpret than traditional methods. The researchers aim to improve disease diagnosis and create customized treatment plans. 

To better understand breast cancer, researchers focus on understanding breast tissue structure and its changes over time. But breast tissue’s complexity and changing structure often make it hard to detect subtle changes using standard imaging techniques. To tackle these hurdles, the research team will develop “TopoQuant,” a suite of informatics tools for breast tissue images.

TopoQuant is built on advanced mathematical modeling and machine learning. The researchers expect to use TopoQuant in collaboration with Stony Brook Medicine clinicians to uncover intricate changes to tissue architecture during cancer pathogenesis, disease progression, and radiation treatment.

The work is supported by a new four-year National Cancer Institute (NCI) $1.2 million grant that runs through August 2028. The team is co-led by Chao Chen, Associate Professor, and Prateek Prasanna, Assistant Professor, from the Department of Biomedical Informatics, both affiliated with the Department of Computer Science. Other collaborators include Alexander Stessin, a clinician in the Department of Radiation Oncology, and Wei Zhao, a breast cancer screening specialist in the Department of Radiology.

To read more about this research, view the full story on Stony Brook News.