Abstract: We present an algorithm for creating high resolution anatomically plausible images that are consistent with acquired clinical brain MRI scans with large inter-slice spacing. Although large databases of clinical images contain a wealth of information, medical acquisition constraints result in sparse scans that miss much of the anatomy. These characteristics often render computational analysis impractical as standard processing algorithms tend to fail when applied to such images.
Mathematical logic was developed in an effort to provide formal foundations
for mathematics. In this quest, which ultimately failed, logic begat
computer science, yielding both computers and theoretical computer science.
But then logic turned out to be a disappointment as foundations for
computer science, as almost all decision problems in logic are either
unsolvable or intractable. Starting from the mid 1970s, however, there
has been a quiet revolution in logic in computer science, and problems that
With the rise of large-scale digitization efforts over the past ten years (such as those by Google Books, the HathiTrust, and the Internet Archive), we now have access to large textual datasets preserving our cultural record in the form of printed books. These text collections have driven research at the intersection of computational methods and the humanities, exploiting advances made over past thirty years in natural language processing and machine learning.
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