Analyzing microtomography data with Python and the scikit-image library

Emmanuelle Gouillart, Juan Nunez-Iglesias, Stéfan Van Der Walt

Research output: Contribution to journalArticleResearchpeer-review

15 Citations (Scopus)

Abstract

The exploration and processing of images is a vital aspect of the scientific workflows of many X-ray imaging modalities. Users require tools that combine interactivity, versatility, and performance. scikit-image is an open-source image processing toolkit for the Python language that supports a large variety of file formats and is compatible with 2D and 3D images. The toolkit exposes a simple programming interface, with thematic modules grouping functions according to their purpose, such as image restoration, segmentation, and measurements. scikit-image users benefit from a rich scientific Python ecosystem that contains many powerful libraries for tasks such as visualization or machine learning. scikit-image combines a gentle learning curve, versatile image processing capabilities, and the scalable performance required for the high-throughput analysis of X-ray imaging data.

Original languageEnglish
Article number18
Number of pages11
JournalAdvanced Structural and Chemical Imaging
Volume2
Issue number1
DOIs
Publication statusPublished - 7 Dec 2016
Externally publishedYes

Keywords

  • 3D image
  • Image processing library
  • Python
  • Scikit-image

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