Detection and Characterization of Lysosomes in Fluorescence Microscopic Images

Wednesday, October 10, 2012 — Poster Session II
Noon – 2:00 p.m	Natcher Conference Center, Building 45	CIT	CELLBIO-8

Authors

• WW Lau
• SB Lioi
• CA Johnson
• JA Mindell

Abstract

Lysosomes are sub-cellular organelles serving as the sewage system in the cell. Lysosomal acidity is an important factor in assuring proper functioning of the enzymes within the organelle, and can be assessed by labeling them with pH-sensitive fluorescence. To enhance our understanding of the variations across the lysosomal population, the goal of this work is to develop a methodology and implement a tool to accurately determine the acidity of each lysosome captured in microscopic images. Several detection algorithms, including multiscale wavelets and 3-D median filtering, have been evaluated using both live-cell and simulated images for which the exact locations and pH values of the spots are known. The processing workflow is implemented in Matlab and can analyze an entire stack of images simultaneously, allowing for the ability to associate the same lysosome across different images. Compared to the commercial software currently used to process the images, our implementation is able to characterize individual organelles in a more automated fashion.

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