Anant Madabhushi, professor of biomedical engineering and director of the Center for Computational Imaging and Personalized Diagnostics, has been awarded U.S. patents 9,235,887 (titled “Classification of Biological Tissue by Multi-mode data registration, segmentation, and characterization”) and 9,235,891 (titled “Boosted Consensus Classifier for Large Images Using Fields of View of Various Sizes”).
U.S. patent 9,235,887 relates to a method and apparatus for classifying possibly vulnerable plaques from sets of DCE-MRI images. The images are processed to determine the boundaries of candidate regions of interest and the voxels within the identified boundaries in corresponding regions of the images from each time period are processed to extract kinetic texture features. The kinetic texture features are then used in a classification process, which classifies the ROIs as vulnerable or stable. Co-inventors include Andrew Buckler, James Hamilton, Shannon Agner and Mark Rosen. The invention has been licensed to Elucid Bioimaging Inc., a Boston-based medical imaging startup company.
U.S. patent 9,235,891 relates to a system and method for predicting disease outcome by analyzing a large, heterogeneous image by a boosted, multi-field-of-view framework, based on image-based features from multi-parametric heterogeneous images. Ajay Basavanhally was co-investigator. The technology has been licensed to Inspirata Inc., a Tampa-based cancer diagnostics company.