Ryoichi Yamakoshi, Kousuke Hirasawa, H. Okuda, H. Kage, K. Sumi, H. Sakamoto, Yuri Ivanov, Toshihiro Yanou, D. Suga, Masao Murakami
{"title":"基于隐式特征的放射治疗对准系统","authors":"Ryoichi Yamakoshi, Kousuke Hirasawa, H. Okuda, H. Kage, K. Sumi, H. Sakamoto, Yuri Ivanov, Toshihiro Yanou, D. Suga, Masao Murakami","doi":"10.1109/ICPR.2010.559","DOIUrl":null,"url":null,"abstract":"In this paper we present a robust alignment algorithm for correcting the effects of out-of-plane rotation to be used for automatic alignment of the Computed Tomography (CT) volumes and the generally low quality fluoroscopic images for radiotherapy applications. Analyzing not only in-plane but also out-of-plane rotation effects on the Dignitary Reconstructed Radiograph (DRR) images, we develop simple alignment algorithm that extracts a set of implicit features from DRR. Using these SIFT-based features, we align DRRs with the fluoroscopic images of the patient and evaluate the alignment accuracy. We compare our approach with traditional techniques based on gradient-based operators and show that our algorithm performs faster while in most cases delivering higher accuracy.","PeriodicalId":309591,"journal":{"name":"2010 20th International Conference on Pattern Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Implicit Feature-Based Alignment System for Radiotherapy\",\"authors\":\"Ryoichi Yamakoshi, Kousuke Hirasawa, H. Okuda, H. Kage, K. Sumi, H. Sakamoto, Yuri Ivanov, Toshihiro Yanou, D. Suga, Masao Murakami\",\"doi\":\"10.1109/ICPR.2010.559\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we present a robust alignment algorithm for correcting the effects of out-of-plane rotation to be used for automatic alignment of the Computed Tomography (CT) volumes and the generally low quality fluoroscopic images for radiotherapy applications. Analyzing not only in-plane but also out-of-plane rotation effects on the Dignitary Reconstructed Radiograph (DRR) images, we develop simple alignment algorithm that extracts a set of implicit features from DRR. Using these SIFT-based features, we align DRRs with the fluoroscopic images of the patient and evaluate the alignment accuracy. We compare our approach with traditional techniques based on gradient-based operators and show that our algorithm performs faster while in most cases delivering higher accuracy.\",\"PeriodicalId\":309591,\"journal\":{\"name\":\"2010 20th International Conference on Pattern Recognition\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-10-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 20th International Conference on Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPR.2010.559\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 20th International Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPR.2010.559","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Implicit Feature-Based Alignment System for Radiotherapy
In this paper we present a robust alignment algorithm for correcting the effects of out-of-plane rotation to be used for automatic alignment of the Computed Tomography (CT) volumes and the generally low quality fluoroscopic images for radiotherapy applications. Analyzing not only in-plane but also out-of-plane rotation effects on the Dignitary Reconstructed Radiograph (DRR) images, we develop simple alignment algorithm that extracts a set of implicit features from DRR. Using these SIFT-based features, we align DRRs with the fluoroscopic images of the patient and evaluate the alignment accuracy. We compare our approach with traditional techniques based on gradient-based operators and show that our algorithm performs faster while in most cases delivering higher accuracy.