The trend toward a quantitative, task based, understanding of medical images leads to the simple goal of answering “how many bits of information would one expect a medical image to contain about disease status?” Knowing the answer to this question could impact a clinician's decision of whether or not to order an imaging study, particularly in the case where it involves ionizing radiation. This quantity can be studied in terms of mutual information between disease status and anatomical form, and is the problem being tackled by Johns Hopkins Kavli NDI researchers, Daniel Tward and Michael Miller.
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At the Kavli NDI we are focused on asking the most tantalizing questions that exist at the intersection of neuroscience, engineering and data science. Kavli NDI News provides a primer on the latest research breakthroughs from Institute members and other progress towards the Institute’s ongoing efforts to answer the questions and challenges facing scientists today.