Emmanuelle Gouillart, Juan Nunez-Iglesias, Stéfan van der Walt
{"title":"用Python和scikit-image库分析微层析成像数据","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":"{\"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}","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}
Analyzing microtomography data with Python and the scikit-image library
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.