{"title":"基于小波变换多尺度积的前列腺超声图像降噪","authors":"Fangwei Zhao, C. Desilva","doi":"10.1109/ANZIIS.2001.974048","DOIUrl":null,"url":null,"abstract":"A noise reduction scheme based on multi-scale products of the dyadic discrete wavelet transform is proposed and a new automatic threshold finding strategy is defined, which assumes no a priori knowledge about the image structure or noise. The preliminary results of applying this scheme to prostate ultrasound images are promising. The important features of the original image are preserved while most of the speckle noise is removed.","PeriodicalId":383878,"journal":{"name":"The Seventh Australian and New Zealand Intelligent Information Systems Conference, 2001","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Noise reduction of ultrasound prostate images using multi-scale products of the wavelet transform\",\"authors\":\"Fangwei Zhao, C. Desilva\",\"doi\":\"10.1109/ANZIIS.2001.974048\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A noise reduction scheme based on multi-scale products of the dyadic discrete wavelet transform is proposed and a new automatic threshold finding strategy is defined, which assumes no a priori knowledge about the image structure or noise. The preliminary results of applying this scheme to prostate ultrasound images are promising. The important features of the original image are preserved while most of the speckle noise is removed.\",\"PeriodicalId\":383878,\"journal\":{\"name\":\"The Seventh Australian and New Zealand Intelligent Information Systems Conference, 2001\",\"volume\":\"48 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Seventh Australian and New Zealand Intelligent Information Systems Conference, 2001\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ANZIIS.2001.974048\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Seventh Australian and New Zealand Intelligent Information Systems Conference, 2001","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ANZIIS.2001.974048","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Noise reduction of ultrasound prostate images using multi-scale products of the wavelet transform
A noise reduction scheme based on multi-scale products of the dyadic discrete wavelet transform is proposed and a new automatic threshold finding strategy is defined, which assumes no a priori knowledge about the image structure or noise. The preliminary results of applying this scheme to prostate ultrasound images are promising. The important features of the original image are preserved while most of the speckle noise is removed.