CHLOE: A Software Tool for Automatic Novelty Detection in Microscopy Image Datasets. Issue 1 (22nd September 2014)

• Record Type: Journal Article
• Authors: Manning, Saundra; Shamir, Lior
• Is Part Of: Journal of open research software. Volume 2:Issue 1(2014)
• Publication Date: 2014-09-22
• Subjects: Image analysis -- Microscopy -- Outlier detection; Computer software -- Reusability -- Periodicals; Open source software -- Periodicals; 005
• DOI: 10.5334/jors.bg
• Languages: English
• ISSNs: 2049-9647

Abstract

The recent advancements in automated microscopy and information systems allow the acquisition and storage of massive datasets of microscopy images. Here we describe CHLOE, a software tool for automatic extraction of novelty in microscopy image datasets. CHLOE is based on a comprehensive set of numerical image content descriptors reflecting image morphology, and can be used in combination with ROI detection and segmentation tools such as ITK. The rich feature set allows automatic detection of repetitive outlier images that are visually different from the common images in the dataset. One of CHLOE 's primary advantages is its versatility, allowing it to detect outlier images in image databases of different subjects and different types of microscopy without modification to the software. The code and software are publicly available for free download athttp://vfacstaff.ltu.edu/lshamir/downloads/chloe .