  Tumors of the eye and nervous system often exhibit an arch-like arrangement
of nuclei, called rosettes. Pathologists are able to identify rosettes [full
circles] and the presence of partial rosettes [semi-circles] and interpret this
as a sign of differentiation in a tumor. However, there is no objective method
to quantitate the many partial rosettes that are obvious or not obvious to the
naked eye. This paper proposes a mathematical algorithm to computationally
detect the presence of obvious or non-obvious partial rosettes, henceforth
referred to as Nguyen-Wu Partial Rosettes. Quantifying the degree of partial
rosettes present in a tumor may allow pathologists to stratify tumors into more
refined groups that may respond better to therapy or have different clinical
outcomes. The Midline Cross Product [MCP] algorithm calculates the magnitude of
two cross products and adds them together to obtain one value. Each of the two
cross products results from [1] the line that connects the midpoints of longest
lengths of two neighboring ovals, and [2] the line that extends from the
midpoint from one longest length and is perpendicular to that longest length.
The MCP algorithm makes nuclei that are arranged in consecutive rows and arches
quantitatively distinct from nuclei that are arranged next to each other in a
disorderly manner.
