{"title":"Kitchen-based light tomography - a DIY toolkit for advancing tomography - by and for the tomography community","authors":"Emanuel Larsson , Doğa Gürsoy , Stephen A. Hall","doi":"10.1016/j.tmater.2022.100001","DOIUrl":null,"url":null,"abstract":"<div><p>We present a recipe for building a portable DIY toolkit, entitled Kitchen-Based Light Tomography (KBLT) for performing tomography using visible light with low-cost and easily accessible components. We also present different use cases to mimic different challenges in tomography, such as imaging time evolving samples. All the software for motor controls, image acquisition, image reconstruction and analysis is open-sourced and available online. The fast acquisition of KBLT datasets permits 4D scanning (3D plus time), also in combination with so-called sample environments, which can support the advancement of improved image reconstruction algorithms. We believe this ‘<em>Do it yourself</em>’ (DIY) toolkit will be useful to tomography users, beamline scientists and computational researchers, and the tomography community in general.</p></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"1 ","pages":"Article 100001"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tomography of Materials and Structures","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949673X22000018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
We present a recipe for building a portable DIY toolkit, entitled Kitchen-Based Light Tomography (KBLT) for performing tomography using visible light with low-cost and easily accessible components. We also present different use cases to mimic different challenges in tomography, such as imaging time evolving samples. All the software for motor controls, image acquisition, image reconstruction and analysis is open-sourced and available online. The fast acquisition of KBLT datasets permits 4D scanning (3D plus time), also in combination with so-called sample environments, which can support the advancement of improved image reconstruction algorithms. We believe this ‘Do it yourself’ (DIY) toolkit will be useful to tomography users, beamline scientists and computational researchers, and the tomography community in general.
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