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Visualization of Parameter Space for Image Analysis
Dec. 2011 (vol. 17 no. 12)
pp. 2402-2411
ASCII Text
x 
 
A. Johannes Pretorius, Mark-Anthony Bray, Anne E. Carpenter, Roy A. Ruddle, "Visualization of Parameter Space for Image Analysis," IEEE Transactions on Visualization and Computer Graphics, vol. 17, no. 12, pp. 2402-2411, Dec., 2011.
 
 
BibTex
x
 
@article{ 10.1109/TVCG.2011.253,
author = {A. Johannes Pretorius and Mark-Anthony Bray and Anne E. Carpenter and Roy A. Ruddle},
title = {Visualization of Parameter Space for Image Analysis},
journal ={IEEE Transactions on Visualization and Computer Graphics},
volume = {17},
number = {12},
issn = {1077-2626},
year = {2011},
pages = {2402-2411},
doi = {http://doi.ieeecomputersociety.org/10.1109/TVCG.2011.253},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Visualization and Computer Graphics
TI - Visualization of Parameter Space for Image Analysis
IS - 12
SN - 1077-2626
SP2402
EP2411
EPD - 2402-2411
A1 - A. Johannes Pretorius,
A1 - Mark-Anthony Bray,
A1 - Anne E. Carpenter,
A1 - Roy A. Ruddle,
PY - 2011
KW - Information visualization
KW - visual analytics
KW - parameter space
KW - image analysis
KW - sampling.
VL - 17
JA - IEEE Transactions on Visualization and Computer Graphics
ER -
 
A. Johannes Pretorius, School of Computing, University of Leeds
Mark-Anthony Bray, Broad Institute of MIT and Harvard
Anne E. Carpenter, Broad Institute of MIT and Harvard
Roy A. Ruddle, School of Computing, University of Leeds
Image analysis algorithms are often highly parameterized and much human input is needed to optimize parameter settings. This incurs a time cost of up to several days. We analyze and characterize the conventional parameter optimization process for image analysis and formulate user requirements. With this as input, we propose a change in paradigm by optimizing parameters based on parameter sampling and interactive visual exploration. To save time and reduce memory load, users are only involved in the first step - initialization of sampling - and the last step - visual analysis of output. This helps users to more thoroughly explore the parameter space and produce higher quality results. We describe a custom sampling plug-in we developed for CellProfiler - a popular biomedical image analysis framework. Our main focus is the development of an interactive visualization technique that enables users to analyze the relationships between sampled input parameters and corresponding output. We implemented this in a prototype called Paramorama. It provides users with a visual overview of parameters and their sampled values. User-defined areas of interest are presented in a structured way that includes image-based output and a novel layout algorithm. To find optimal parameter settings, users can tag high- and low-quality results to refine their search. We include two case studies to illustrate the utility of this approach.

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Index Terms:
Information visualization, visual analytics, parameter space, image analysis, sampling.
Citation:
A. Johannes Pretorius, Mark-Anthony Bray, Anne E. Carpenter, Roy A. Ruddle, "Visualization of Parameter Space for Image Analysis," IEEE Transactions on Visualization and Computer Graphics, vol. 17, no. 12, pp. 2402-2411, Dec. 2011, doi:10.1109/TVCG.2011.253
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