Analyzing microtomography data with Python and the scikit-image library.

Journal: Advanced structural and chemical imaging
Published Date:

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.

Authors

  • Emmanuelle Gouillart
    Surface du Verre et Interfaces, UMR 125 CNRS/Saint-Gobain, 93303 Aubervilliers, France.
  • Juan Nunez-Iglesias
    Victorian Life Sciences Computation Initiative, University of Melbourne, Carlton, VIC Australia.
  • Stéfan van der Walt
    Division of Applied Mathematics, Stellenbosch University, Stellenbosch, South Africa.

Keywords

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