Information Processing for Medical Image Understanding

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This research program can be phrased as a simple question: ``How can computer science improve a physician's understanding of disease processes?'' In the proposed work, novel displays of complex information will provide tools for exploring metabolic processes and guiding a surgeon to excise all of a cancerous tumor; in orthopedics, improved mathematical modeling will be used to address the highly variable presentation of osteoarthritis in medical images. This proposal is to use the applicant's expertise in computing, and considerable experience in surgery, to give new theoretical results and implementations that will directly improve the health of Canadians.***The novel displays will include the auditory presentation of data from mass spectrometry. At Queen's, we have several instruments that can variously capture mass-spectrometry images of tissue, or can capture a data stream as a surgical electric knife slices through tissue. These data are highly multi-spectral and are very difficult to classify automatically. Instead, I propose to transform the mass data to an audible output. This will let a pathologist studying a tissue sample, or a surgeon making real-time decisions in an operating room, to literally hear the sound of cancer. Being able to hear the metabolic products of each cell in a sample would be a world-leading breakthrough in the analysis of tissues for cancer research.***The mathematical modeling will include ways to perform computations on high-dimension mathematical manifolds. First, we will develop statistical models of arthritic joints based on the manifolds; next, we will use the statistical models to improve the automatic recognition of arthritic joints in 3D images such as CT or MRI scans. Arthritis is a constellation of diseases that affects nearly every Canadian family, so improved ways of describing it will help the staging of treatments for this debilitating condition.***Twenty-four highly qualified personnel will receive multidisciplinary training to prepare them for careers in biomedical computing. Our graduates are highly sought after by medical schools, graduate schools, and information-technology industry sectors.