Emmanuelle Gouillart, Juan Nunez-Iglesias, Stéfan van der Walt
{"title":"Analyzing microtomography data with Python and the scikit-image library","authors":"Emmanuelle Gouillart, Juan Nunez-Iglesias, Stéfan van der Walt","doi":"10.1186/s40679-016-0031-0","DOIUrl":null,"url":null,"abstract":"<p>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. <span>scikit-image</span> 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. <span>scikit-image</span> users benefit from a rich scientific Python ecosystem that contains many powerful libraries for tasks such as visualization or machine learning. <span>scikit-image</span> combines a gentle learning curve, versatile image processing capabilities, and the scalable performance required for the high-throughput analysis of X-ray imaging data.</p>","PeriodicalId":460,"journal":{"name":"Advanced Structural and Chemical Imaging","volume":"2 1","pages":""},"PeriodicalIF":3.5600,"publicationDate":"2016-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40679-016-0031-0","citationCount":"24","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Structural and Chemical Imaging","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1186/s40679-016-0031-0","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 24
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.