{"title":"用于PACS的乳房x光图像JPEG量化矩阵优化","authors":"D. Campbell, A. Maeder, F. Tapia-Vergara","doi":"10.1109/ANZIIS.2001.974038","DOIUrl":null,"url":null,"abstract":"Clinical procedures and legal requirements increasingly demand greater performance in JPEG compression of digitised grayscale medical images without loss of visual fidelity or without exceeding a bounded error metric. Current JPEG common practice uses a default general-purpose luminance quantisation matrix. As an initial investigation into defining more suitable quantisation matrices for different medical image modalities, a new candidate matrix has been derived for mammograms. For a given SNR, the new quantisation matrix achieves a relative compression ratio performance improvement of approximately 22% for a quality factor of 95% and 15% for a quality factor of 85%. This study paves the way for a computationally intelligent approach to optimising the quantisation matrix for each medical image modality in both batch mode and adaptively on an image-by-image basis.","PeriodicalId":383878,"journal":{"name":"The Seventh Australian and New Zealand Intelligent Information Systems Conference, 2001","volume":"197 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Mammogram JPEG quantisation matrix optimisation for PACS\",\"authors\":\"D. Campbell, A. Maeder, F. Tapia-Vergara\",\"doi\":\"10.1109/ANZIIS.2001.974038\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Clinical procedures and legal requirements increasingly demand greater performance in JPEG compression of digitised grayscale medical images without loss of visual fidelity or without exceeding a bounded error metric. Current JPEG common practice uses a default general-purpose luminance quantisation matrix. As an initial investigation into defining more suitable quantisation matrices for different medical image modalities, a new candidate matrix has been derived for mammograms. For a given SNR, the new quantisation matrix achieves a relative compression ratio performance improvement of approximately 22% for a quality factor of 95% and 15% for a quality factor of 85%. This study paves the way for a computationally intelligent approach to optimising the quantisation matrix for each medical image modality in both batch mode and adaptively on an image-by-image basis.\",\"PeriodicalId\":383878,\"journal\":{\"name\":\"The Seventh Australian and New Zealand Intelligent Information Systems Conference, 2001\",\"volume\":\"197 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"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.2001.974038\",\"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.2001.974038","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mammogram JPEG quantisation matrix optimisation for PACS
Clinical procedures and legal requirements increasingly demand greater performance in JPEG compression of digitised grayscale medical images without loss of visual fidelity or without exceeding a bounded error metric. Current JPEG common practice uses a default general-purpose luminance quantisation matrix. As an initial investigation into defining more suitable quantisation matrices for different medical image modalities, a new candidate matrix has been derived for mammograms. For a given SNR, the new quantisation matrix achieves a relative compression ratio performance improvement of approximately 22% for a quality factor of 95% and 15% for a quality factor of 85%. This study paves the way for a computationally intelligent approach to optimising the quantisation matrix for each medical image modality in both batch mode and adaptively on an image-by-image basis.