Research

Wndchrm – an open source utility for biological image analysis

Lior Shamir¹ , Nikita Orlov¹ , D Mark Eckley¹ , Tomasz Macura^1,2 , Josiah Johnston³ and Ilya G Goldberg¹

¹  Image Informatics and Computational Biology Unit, Laboratory of Genetics, NIA/NIH, 333 Cassell Dr., Baltimore, MD, 21224, USA

²  Computer Laboratory, University of Cambridge, 15 Thomson Avenue, Cambridge, UK

³  Energy and Resources Group, University of California Berkeley, 1519 Addison St., Berkeley, CA, 94720-3050, USA

author email corresponding author email

Source Code for Biology and Medicine 2008, 3:13doi:10.1186/1751-0473-3-13

Published:	8 July 2008

Abstract

Background

Biological imaging is an emerging field, covering a wide range of applications in biological and clinical research. However, while machinery for automated experimenting and data acquisition has been developing rapidly in the past years, automated image analysis often introduces a bottleneck in high content screening.

Methods

Wndchrm is an open source utility for biological image analysis. The software works by first extracting image content descriptors from the raw image, image transforms, and compound image transforms. Then, the most informative features are selected, and the feature vector of each image is used for classification and similarity measurement.

Results

Wndchrm has been tested using several publicly available biological datasets, and provided results which are favorably comparable to the performance of task-specific algorithms developed for these datasets. The simple user interface allows researchers who are not knowledgeable in computer vision methods and have no background in computer programming to apply image analysis to their data.

Conclusion

We suggest that wndchrm can be effectively used for a wide range of biological image analysis tasks. Using wndchrm can allow scientists to perform automated biological image analysis while avoiding the costly challenge of implementing computer vision and pattern recognition algorithms.