{"title":"Medical image watermarking for multiple modalities","authors":"A. Maeder, B. Planitz","doi":"10.1109/AIPR.2005.33","DOIUrl":null,"url":null,"abstract":"Transfer of digital medical images between multiple parties requires the assurance of image identity and integrity, which can be achieved through image watermarking. This raises concerns for loss in viewer performance due to degradation of image quality. Here we describe an approach to ensure that impact on the image quality is well below the threshold of visual perceptibility. The principles on which this approach rests are the choice of a suitably light payload, and the use of different watermarking methods and parameters for different medical image types. We provide examples of this approach applied to MR, CT and CR images","PeriodicalId":130204,"journal":{"name":"34th Applied Imagery and Pattern Recognition Workshop (AIPR'05)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"34th Applied Imagery and Pattern Recognition Workshop (AIPR'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIPR.2005.33","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
Transfer of digital medical images between multiple parties requires the assurance of image identity and integrity, which can be achieved through image watermarking. This raises concerns for loss in viewer performance due to degradation of image quality. Here we describe an approach to ensure that impact on the image quality is well below the threshold of visual perceptibility. The principles on which this approach rests are the choice of a suitably light payload, and the use of different watermarking methods and parameters for different medical image types. We provide examples of this approach applied to MR, CT and CR images