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Sato, Y., Nakajima, S., Shiraga, N., Atsumi, H., Yoshida, S., Koller, T., Gerig, G. and Kikinis, R. (1998) Three-Dimensional Multi-Scale Line Filters for Segmentation and Visualization of Curvilinear Structures in Medical Images. Medical Image Analysis, 2, 143-168.
http://dx.doi.org/10.1016/S1361-8415(98)80009-1
has been cited by the following article:
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TITLE:
Determination of Statistical Properties of Microtubule Populations
AUTHORS:
Tyson DiLorenzo, Lee Ligon, Donald Drew
KEYWORDS:
Microtubule, Image Analysis, Curvature
JOURNAL NAME:
Applied Mathematics,
Vol.7 No.13,
August
15,
2016
ABSTRACT: Microtubules are structures within the cell
that form a transportation network along which motor proteins tow cargo to
destinations. To establish and maintain a structure capable of serving the
cell’s tasks, microtubules undergo deconstruction and reconstruction regularly.
This change in structure is critical to tasks like wound repair and cell
motility. Images of fluorescing microtubule networks are captured in grayscale
at different wavelengths, displaying different tagged proteins. The analysis of
these polymeric structures involves identifying the presence of the protein and
the direction of the structure in which it resides. This study considers the
problem of finding statistical properties of sections of microtubules. We
consider the research done on directional filters and utilize a basic solution
to find the center of a ridge. The method processes the captured image by
centering a circle around pre-determined pixel locations so that the highest
possible average pixel intensity is found within the circle, thus marking the
center of the microtubule. The location of these centers allows us to estimate
angular direction and curvature of the microtubules, statistically estimate the
direction of microtubules in a region of the cell, and compare properties of
different types of microtubule networks in the same region. To verify accuracy,
we study the results of the method on a test image.