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Proceedings Paper

Computer assisted analysis of microscopy images
Author(s): M. Sawicki; P. Munhutu; J. DaPonte; C. Caragianis-Broadbridge; A. Lehman; T. Sadowski; E. Garcia; C. Heyden; L. Mirabelle; P. Benjamin
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Paper Abstract

The use of Transmission Electron Microscopy (TEM) to characterize the microstructure of a material continues to grow in importance as technological advancements become increasingly more dependent on nanotechnology1 . Since nanoparticle properties such as size (diameter) and size distribution are often important in determining potential applications, a particle analysis is often performed on TEM images. Traditionally done manually, this has the potential to be labor intensive, time consuming, and subjective2. To resolve these issues, automated particle analysis routines are becoming more widely accepted within the community3. When using such programs, it is important to compare their performance, in terms of functionality and cost. The primary goal of this study was to apply one such software package, ImageJ to grayscale TEM images of nanoparticles with known size. A secondary goal was to compare this popular open-source general purpose image processing program to two commercial software packages. After a brief investigation of performance and price, ImageJ was identified as the software best suited for the particle analysis conducted in the study. While many ImageJ functions were used, the ability to break agglomerations that occur in specimen preparation into separate particles using a watershed algorithm was particularly helpful4.

Paper Details

Date Published: 20 January 2009
PDF: 9 pages
Proc. SPIE 7243, Visualization and Data Analysis 2009, 724305 (20 January 2009); doi: 10.1117/12.805613
Show Author Affiliations
M. Sawicki, Southern Connecticut State Univ. (United States)
P. Munhutu, Southern Connecticut State Univ. (United States)
J. DaPonte, Southern Connecticut State Univ. (United States)
C. Caragianis-Broadbridge, Southern Connecticut State Univ. (United States)
A. Lehman, Trinity College (United States)
Southern Connecticut State Univ. (United States)
T. Sadowski, Southern Connecticut State Univ. (United States)
E. Garcia, Southern Connecticut State Univ. (United States)
C. Heyden, Southern Connecticut State Univ. (United States)
L. Mirabelle, Southern Connecticut State Univ. (United States)
P. Benjamin, Southern Connecticut State Univ. (United States)


Published in SPIE Proceedings Vol. 7243:
Visualization and Data Analysis 2009
Katy Börner; Jinah Park, Editor(s)

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