chloe: a software tool for automatic novelty detection in microscopy image datasets

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2014
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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. The tool 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. The code and software are publicly available for free download at http://vfacstaff.ltu.edu/lshamir/downloads/chloe.
Reference Key
manning2014journalchloe: Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Saundra Manning;Lior Shamir
Journal society of petroleum engineers - spe international heavy oil conference and exhibition 2018, hoce 2018
Year 2014
DOI
10.5334/jors.bg
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