A. Munteanu, J. Cornelis, P. De Muynck, Anastasios Bezerianos, P. Cristea
{"title":"用连续小波变换精确检测冠状动脉","authors":"A. Munteanu, J. Cornelis, P. De Muynck, Anastasios Bezerianos, P. Cristea","doi":"10.1109/CIC.1997.648121","DOIUrl":null,"url":null,"abstract":"The authors propose a multi-scale detection scheme of the vessels borders by means of the continuous wavelet transform. The Canny's (1986) performance parameters are derived for Mallat's (1992) wavelet based edge detection operator. The authors take the scale dependent behaviour of these parameters into account to design an algorithm that optimally combines the multiscale information. Evaluation of the algorithm accuracy is obtained on 4 vessel phantoms of different diameters. The authors compare the computer determined diameters to the actual diameters, the correlation coefficient is in the range 0.93-0.99 for different types of wavelets, which proves the ability of the method to accurately detect edges in the presence of noise.","PeriodicalId":228649,"journal":{"name":"Computers in Cardiology 1997","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Accurate detection of coronary arteries with the continuous wavelet transform\",\"authors\":\"A. Munteanu, J. Cornelis, P. De Muynck, Anastasios Bezerianos, P. Cristea\",\"doi\":\"10.1109/CIC.1997.648121\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The authors propose a multi-scale detection scheme of the vessels borders by means of the continuous wavelet transform. The Canny's (1986) performance parameters are derived for Mallat's (1992) wavelet based edge detection operator. The authors take the scale dependent behaviour of these parameters into account to design an algorithm that optimally combines the multiscale information. Evaluation of the algorithm accuracy is obtained on 4 vessel phantoms of different diameters. The authors compare the computer determined diameters to the actual diameters, the correlation coefficient is in the range 0.93-0.99 for different types of wavelets, which proves the ability of the method to accurately detect edges in the presence of noise.\",\"PeriodicalId\":228649,\"journal\":{\"name\":\"Computers in Cardiology 1997\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-09-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers in Cardiology 1997\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIC.1997.648121\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers in Cardiology 1997","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIC.1997.648121","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Accurate detection of coronary arteries with the continuous wavelet transform
The authors propose a multi-scale detection scheme of the vessels borders by means of the continuous wavelet transform. The Canny's (1986) performance parameters are derived for Mallat's (1992) wavelet based edge detection operator. The authors take the scale dependent behaviour of these parameters into account to design an algorithm that optimally combines the multiscale information. Evaluation of the algorithm accuracy is obtained on 4 vessel phantoms of different diameters. The authors compare the computer determined diameters to the actual diameters, the correlation coefficient is in the range 0.93-0.99 for different types of wavelets, which proves the ability of the method to accurately detect edges in the presence of noise.