M. Sasso, M. Talmant, G. Haiat, P. Laugier, S. Naili
{"title":"Development of a Multi-Dimensional SVD based Technique for Multi-Receivers Ultrasound used in Bone Status Characterization","authors":"M. Sasso, M. Talmant, G. Haiat, P. Laugier, S. Naili","doi":"10.1109/SAM.2006.1706217","DOIUrl":null,"url":null,"abstract":"The use of multi-dimensional wave extraction algorithm for a multi-receivers axial transmission ultrasound device used in bone evaluation is proposed. As far as we know, multi-dimensional signal processing techniques have never been implemented in this configuration. A SVD-based wavefront extraction is implemented for the characterization of an energetic low frequency contribution. Velocity accuracy is estimated on a synthetic dataset. Furthermore, the energetic low frequency removal is illustrated on in vivo signals. Results are promising as for the application of multi-dimensional techniques in medical ultrasound used in transmission","PeriodicalId":272327,"journal":{"name":"Fourth IEEE Workshop on Sensor Array and Multichannel Processing, 2006.","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fourth IEEE Workshop on Sensor Array and Multichannel Processing, 2006.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAM.2006.1706217","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The use of multi-dimensional wave extraction algorithm for a multi-receivers axial transmission ultrasound device used in bone evaluation is proposed. As far as we know, multi-dimensional signal processing techniques have never been implemented in this configuration. A SVD-based wavefront extraction is implemented for the characterization of an energetic low frequency contribution. Velocity accuracy is estimated on a synthetic dataset. Furthermore, the energetic low frequency removal is illustrated on in vivo signals. Results are promising as for the application of multi-dimensional techniques in medical ultrasound used in transmission