Work in our group focuses on developing innovative image analysis, machine learning and data science methodologies for multimodality imaging, and also on incorporating such methods into clinically relevant applications. To this end, we have developed innovative computational methodologies that have enabled the investigation of novel phenotypic biomarkers via imaging, as well as translating these biomarkers through large clinical and epidemiological studies, to address relevant research questions for personalizing breast cancer care.
Specific thematic areas of research include the emerging fields of “radiomics/radiogenomics”, investigating both the association of such phenotypic imaging markers with genetic markers well as their potential to augment current standard clinical assessment, and most importantly emerging molecular and histopathologic biomarkers in breast cancer risk assessment, determining prognosis, and predicting patient therapy response and survival.
Most of our work to date has been on breast imaging, with recent expansion in to oncologic imaging, including lung and molecular imaging applications.
Learn more about our approaches and methods focusing on investigation into the role of image analysis and quantitative imaging as a biomarker for improving personalized clinical decisions for cancer screening, prognostication and treatment.
Overview of the awards and grants CBIG has received through extramural funding from both federal agencies and private foundations. Support sources include the National Institutes of Health (NIH), the Department of Defense (DOD), the American Cancer Society (ACS), and the Radiological Society of North America (RSNA).