I. H. Arka, K. Chellappan, S. Mukari, Z. Law, R. Sahathevan, Ashrani Aizzuddin Abd Rahni
{"title":"同时倾斜校正和配准的CT血管成像和动态CT脑图像","authors":"I. H. Arka, K. Chellappan, S. Mukari, Z. Law, R. Sahathevan, Ashrani Aizzuddin Abd Rahni","doi":"10.1109/ICBAPS.2015.7292224","DOIUrl":null,"url":null,"abstract":"In this paper we present a pre-processing stage for an automated volumetric CT stroke image diagnosis system. It concerns the automatic intensity-based 3D image registration of dynamic CT (used for CT perfusion imaging) to CT angiography (CTA) images. The dynamic CT images were acquired with a gantry tilt and hence the correct geometry is found. The tilt correction is performed implicitly and combined with intensity based registration to the CTA image. The accuracy of image registration is measured by the overlap of the segmented skull from both images. The results are promising with more efficient implementation in future for clinical feasibility.","PeriodicalId":243293,"journal":{"name":"2015 International Conference on BioSignal Analysis, Processing and Systems (ICBAPS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Simultaneous tilt correction and registration of CT angiography and dynamic CT brain images\",\"authors\":\"I. H. Arka, K. Chellappan, S. Mukari, Z. Law, R. Sahathevan, Ashrani Aizzuddin Abd Rahni\",\"doi\":\"10.1109/ICBAPS.2015.7292224\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we present a pre-processing stage for an automated volumetric CT stroke image diagnosis system. It concerns the automatic intensity-based 3D image registration of dynamic CT (used for CT perfusion imaging) to CT angiography (CTA) images. The dynamic CT images were acquired with a gantry tilt and hence the correct geometry is found. The tilt correction is performed implicitly and combined with intensity based registration to the CTA image. The accuracy of image registration is measured by the overlap of the segmented skull from both images. The results are promising with more efficient implementation in future for clinical feasibility.\",\"PeriodicalId\":243293,\"journal\":{\"name\":\"2015 International Conference on BioSignal Analysis, Processing and Systems (ICBAPS)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on BioSignal Analysis, Processing and Systems (ICBAPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICBAPS.2015.7292224\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on BioSignal Analysis, Processing and Systems (ICBAPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICBAPS.2015.7292224","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Simultaneous tilt correction and registration of CT angiography and dynamic CT brain images
In this paper we present a pre-processing stage for an automated volumetric CT stroke image diagnosis system. It concerns the automatic intensity-based 3D image registration of dynamic CT (used for CT perfusion imaging) to CT angiography (CTA) images. The dynamic CT images were acquired with a gantry tilt and hence the correct geometry is found. The tilt correction is performed implicitly and combined with intensity based registration to the CTA image. The accuracy of image registration is measured by the overlap of the segmented skull from both images. The results are promising with more efficient implementation in future for clinical feasibility.