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BMCBI
2016

CP-CHARM: segmentation-free image classification made accessible

8 years 3 months ago
CP-CHARM: segmentation-free image classification made accessible
Background: Automated classification using machine learning often relies on features derived from segmenting individual objects, which can be difficult to automate. WND-CHARM is a previously developed classification algorithm in which features are computed on the whole image, thereby avoiding the need for segmentation. The algorithm obtained encouraging results but requires considerable computational expertise to execute. Furthermore, some benchmark sets have been shown to be subject to confounding artifacts that overestimate classification accuracy. Results: We developed CP-CHARM, a user-friendly image-based classification algorithm inspired by WND-CHARM in (i) its ability to capture a wide variety of morphological aspects of the image, and (ii) the absence of requirement for segmentation. In order to make such an image-based classification method easily accessible to the biological research community, CP-CHARM relies on the widely-used open-source image analysis software CellProfile...
Virginie Uhlmann, Shantanu Singh, Anne E. Carpente
Added 30 Mar 2016
Updated 30 Mar 2016
Type Journal
Year 2016
Where BMCBI
Authors Virginie Uhlmann, Shantanu Singh, Anne E. Carpenter
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