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Some biologists are interested in basal bodies.
By Dartmouth Electron Microscope Facility, Dartmouth College - Source and public domain notice at http://remf.dartmouth.edu/imagesindex.html, Public Domain, https://commons.wikimedia.org/w/index.php?curid=2787228
They study how abnormalities in the spatial distribution of basal bodies affect the proper functioning of ciliates.
By Robinson R (2006) Ciliate Genome Sequence Reveals Unique Features of a Model Eukaryote. PLoS Biol 4(9): e304. doi:10.1371/journal.pbio.0040304, CC BY 2.5, https://commons.wikimedia.org/w/index.php?curid=1479145
In order to talk about "abnormalities", we first need to establish a well-defined notion of what it means to be "normal" (i.e. what our baseline for comparison is).
One way that we can do this is by building statistical models of the spatial distribution of basal bodies. Such models provide us with a framework for quantifying how different the basal body distribution of any given cell is from that of an "average" cell (which for modeling purposes we take to be the ideal) of the same species.
This project is about capturing the geometry of basal bodies by analyzing microscopy images.
- Image segmentation
In this context, the problem can be reduced to histogram thresholding with the objective of doing at least as well as a human.
The images are noisy, not on the scale that humans would describe as "glaring", but on a scale which complicates traditional segmentation pipelines. I think that the Weber-Fechner law may actually be worth thinking about in developing a suitable segmentation pipeline.
- Clustering
We need to group points (basal bodies) into clusters that resemble curves (ciliary rows). The main issue is that inter-cluster and intra-cluster distances are indistinguishable at particular region of cell.
We probably have to apply different clustering rules for different regions of the cell, and then later merge these clusters accordingly.
If (1) is not performed well, the success of (2) will very much be compromised.
To be continued ...