Ryoichi Yamakoshi, Kousuke Hirasawa, H. Okuda, H. Kage, K. Sumi, H. Sakamoto, Yuri Ivanov, Toshihiro Yanou, D. Suga, Masao Murakami
{"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":null,"pages":null},"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}
引用次数: 1
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.