{"title":"超声图像单图像超分辨率方法的实现","authors":"Ezgi Kupcuoglu Yasin, H. Ş. Bilge","doi":"10.1109/SIU55565.2022.9864888","DOIUrl":null,"url":null,"abstract":"Today, image quality has become an important factor in many areas. Especially in the field of medical imaging, high-resolution images are needed. In this study, EDSR (Enhanced Deep Residual Networks for Single Image Super-Resolution) and DCSCN (Fast and Accurate Image Super-Resolution by Deep Convolutional Neural Network with Skip Connection and Network in Network) methods were trained using the ultrasound dataset and the results were compared, considering the need for high resolution images in the medical field.","PeriodicalId":115446,"journal":{"name":"2022 30th Signal Processing and Communications Applications Conference (SIU)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Implementation of Single Image Super-Resolution Methods on Ultrasound Images\",\"authors\":\"Ezgi Kupcuoglu Yasin, H. Ş. Bilge\",\"doi\":\"10.1109/SIU55565.2022.9864888\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Today, image quality has become an important factor in many areas. Especially in the field of medical imaging, high-resolution images are needed. In this study, EDSR (Enhanced Deep Residual Networks for Single Image Super-Resolution) and DCSCN (Fast and Accurate Image Super-Resolution by Deep Convolutional Neural Network with Skip Connection and Network in Network) methods were trained using the ultrasound dataset and the results were compared, considering the need for high resolution images in the medical field.\",\"PeriodicalId\":115446,\"journal\":{\"name\":\"2022 30th Signal Processing and Communications Applications Conference (SIU)\",\"volume\":\"64 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 30th Signal Processing and Communications Applications Conference (SIU)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SIU55565.2022.9864888\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 30th Signal Processing and Communications Applications Conference (SIU)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIU55565.2022.9864888","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
如今，图像质量已成为许多领域的重要因素。特别是在医学成像领域，需要高分辨率的图像。本研究针对医学领域对高分辨率图像的需求，利用超声数据集对EDSR (Enhanced Deep Residual Networks for Single Image superresolution)和DCSCN (Fast and Accurate Image superresolution by Deep Convolutional Neural Network with Skip Connection and Network In Network)方法进行训练，并对结果进行比较。
Implementation of Single Image Super-Resolution Methods on Ultrasound Images
Today, image quality has become an important factor in many areas. Especially in the field of medical imaging, high-resolution images are needed. In this study, EDSR (Enhanced Deep Residual Networks for Single Image Super-Resolution) and DCSCN (Fast and Accurate Image Super-Resolution by Deep Convolutional Neural Network with Skip Connection and Network in Network) methods were trained using the ultrasound dataset and the results were compared, considering the need for high resolution images in the medical field.
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