A. Danudibroto, J. Bersvendsen, O. Mirea, O. Gérard, J. D’hooge, E. Samset
{"title":"超声心动图序列的基于图像的时间对齐","authors":"A. Danudibroto, J. Bersvendsen, O. Mirea, O. Gérard, J. D’hooge, E. Samset","doi":"10.1117/12.2216192","DOIUrl":null,"url":null,"abstract":"Temporal alignment of echocardiographic sequences enables fair comparisons of multiple cardiac sequences by showing corresponding frames at given time points in the cardiac cycle. It is also essential for spatial registration of echo volumes where several acquisitions are combined for enhancement of image quality or forming larger field of view. In this study, three different image-based temporal alignment methods were investigated. First, a method based on dynamic time warping (DTW). Second, a spline-based method that optimized the similarity between temporal characteristic curves of the cardiac cycle using 1D cubic B-spline interpolation. Third, a method based on the spline-based method with piecewise modification. These methods were tested on in-vivo data sets of 19 echo sequences. For each sequence, the mitral valve opening (MVO) time was manually annotated. The results showed that the average MVO timing error for all methods are well under the time resolution of the sequences.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Image-based temporal alignment of echocardiographic sequences\",\"authors\":\"A. Danudibroto, J. Bersvendsen, O. Mirea, O. Gérard, J. D’hooge, E. Samset\",\"doi\":\"10.1117/12.2216192\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Temporal alignment of echocardiographic sequences enables fair comparisons of multiple cardiac sequences by showing corresponding frames at given time points in the cardiac cycle. It is also essential for spatial registration of echo volumes where several acquisitions are combined for enhancement of image quality or forming larger field of view. In this study, three different image-based temporal alignment methods were investigated. First, a method based on dynamic time warping (DTW). Second, a spline-based method that optimized the similarity between temporal characteristic curves of the cardiac cycle using 1D cubic B-spline interpolation. Third, a method based on the spline-based method with piecewise modification. These methods were tested on in-vivo data sets of 19 echo sequences. For each sequence, the mitral valve opening (MVO) time was manually annotated. The results showed that the average MVO timing error for all methods are well under the time resolution of the sequences.\",\"PeriodicalId\":228011,\"journal\":{\"name\":\"SPIE Medical Imaging\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SPIE Medical Imaging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2216192\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SPIE Medical Imaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2216192","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Image-based temporal alignment of echocardiographic sequences
Temporal alignment of echocardiographic sequences enables fair comparisons of multiple cardiac sequences by showing corresponding frames at given time points in the cardiac cycle. It is also essential for spatial registration of echo volumes where several acquisitions are combined for enhancement of image quality or forming larger field of view. In this study, three different image-based temporal alignment methods were investigated. First, a method based on dynamic time warping (DTW). Second, a spline-based method that optimized the similarity between temporal characteristic curves of the cardiac cycle using 1D cubic B-spline interpolation. Third, a method based on the spline-based method with piecewise modification. These methods were tested on in-vivo data sets of 19 echo sequences. For each sequence, the mitral valve opening (MVO) time was manually annotated. The results showed that the average MVO timing error for all methods are well under the time resolution of the sequences.