{"title":"基于LSTM网络的医学图像有损压缩","authors":"G. N. Prabhu, Trisiladevi C. Nagavi, P. Mahesha","doi":"10.4018/978-1-5225-6316-7.CH003","DOIUrl":null,"url":null,"abstract":"Medical images have a larger size when compared to normal images. There arises a problem in the storage as well as in the transmission of a large number of medical images. Hence, there exists a need for compressing these images to reduce the size as much as possible and also to maintain a better quality. The authors propose a method for lossy image compression of a set of medical images which is based on Recurrent Neural Network (RNN). So, the proposed method produces images of variable compression rates to maintain the quality aspect and to preserve some of the important contents present in these images.","PeriodicalId":104783,"journal":{"name":"Histopathological Image Analysis in Medical Decision Making","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Medical Image Lossy Compression With LSTM Networks\",\"authors\":\"G. N. Prabhu, Trisiladevi C. Nagavi, P. Mahesha\",\"doi\":\"10.4018/978-1-5225-6316-7.CH003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Medical images have a larger size when compared to normal images. There arises a problem in the storage as well as in the transmission of a large number of medical images. Hence, there exists a need for compressing these images to reduce the size as much as possible and also to maintain a better quality. The authors propose a method for lossy image compression of a set of medical images which is based on Recurrent Neural Network (RNN). So, the proposed method produces images of variable compression rates to maintain the quality aspect and to preserve some of the important contents present in these images.\",\"PeriodicalId\":104783,\"journal\":{\"name\":\"Histopathological Image Analysis in Medical Decision Making\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Histopathological Image Analysis in Medical Decision Making\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/978-1-5225-6316-7.CH003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Histopathological Image Analysis in Medical Decision Making","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/978-1-5225-6316-7.CH003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Medical Image Lossy Compression With LSTM Networks
Medical images have a larger size when compared to normal images. There arises a problem in the storage as well as in the transmission of a large number of medical images. Hence, there exists a need for compressing these images to reduce the size as much as possible and also to maintain a better quality. The authors propose a method for lossy image compression of a set of medical images which is based on Recurrent Neural Network (RNN). So, the proposed method produces images of variable compression rates to maintain the quality aspect and to preserve some of the important contents present in these images.