K. Ntatsis, Niels Dekker, Viktor van der Valk, Tom Birdsong, Dženan Zukić, S. Klein, M. Staring, Matthew Mccormick
{"title":"itk-elastix: Python医学图像配准","authors":"K. Ntatsis, Niels Dekker, Viktor van der Valk, Tom Birdsong, Dženan Zukić, S. Klein, M. Staring, Matthew Mccormick","doi":"10.25080/gerudo-f2bc6f59-00d","DOIUrl":null,"url":null,"abstract":"—Image registration plays a vital role in understanding changes that occur in 2D and 3D scientific imaging datasets. Registration involves finding a spatial transformation that aligns one image to another by optimizing relevant image similarity metrics. In this paper, we introduce itk-elastix , a user-friendly Python wrapping of the mature elastix registration toolbox. The open-source tool supports rigid, affine, and B-spline deformable registration, making it versatile for various imaging datasets. By utilizing the modular de-sign of itk-elastix , users can efficiently configure and compare different registration methods, and embed these in image analysis workflows.","PeriodicalId":364654,"journal":{"name":"Proceedings of the Python in Science Conference","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"itk-elastix: Medical image registration in Python\",\"authors\":\"K. Ntatsis, Niels Dekker, Viktor van der Valk, Tom Birdsong, Dženan Zukić, S. Klein, M. Staring, Matthew Mccormick\",\"doi\":\"10.25080/gerudo-f2bc6f59-00d\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"—Image registration plays a vital role in understanding changes that occur in 2D and 3D scientific imaging datasets. Registration involves finding a spatial transformation that aligns one image to another by optimizing relevant image similarity metrics. In this paper, we introduce itk-elastix , a user-friendly Python wrapping of the mature elastix registration toolbox. The open-source tool supports rigid, affine, and B-spline deformable registration, making it versatile for various imaging datasets. By utilizing the modular de-sign of itk-elastix , users can efficiently configure and compare different registration methods, and embed these in image analysis workflows.\",\"PeriodicalId\":364654,\"journal\":{\"name\":\"Proceedings of the Python in Science Conference\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Python in Science Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.25080/gerudo-f2bc6f59-00d\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Python in Science Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25080/gerudo-f2bc6f59-00d","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
—Image registration plays a vital role in understanding changes that occur in 2D and 3D scientific imaging datasets. Registration involves finding a spatial transformation that aligns one image to another by optimizing relevant image similarity metrics. In this paper, we introduce itk-elastix , a user-friendly Python wrapping of the mature elastix registration toolbox. The open-source tool supports rigid, affine, and B-spline deformable registration, making it versatile for various imaging datasets. By utilizing the modular de-sign of itk-elastix , users can efficiently configure and compare different registration methods, and embed these in image analysis workflows.