“ Nothing in life is to be feared, it is only to be understood. Now is the time to understand more, so that we may fear less. ”

Marie Curie


Kavli NDI News

Developing “codewords” to characterize the complexity of human anatomy at clinically relevant scales

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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