{"title":"基于高斯平滑卷积滤波器的子宫肌瘤超声图像去噪","authors":"M. Devi, V. Sindhu","doi":"10.38124/ijisrt20jul768","DOIUrl":null,"url":null,"abstract":"This paper discusses the methods to detect the presence of uterus fibroid in woman by implementing various image processing techniques. The input image is an ultrasound image as it is cost effective when compared to other imaging techniques like CT, MRI. The initial step in image processing is to remove noise by applying filters. Application of filters smoothen the image without blurring the image. Gradient of the processed image is calculated and the image is enhanced by sharpening the edges of the image are achieved by calculating the local maxima of the gradient. Then, the edges are decided by calculating the threshold value of the processed image. The proposed Gaussismooth Convolution Filter gives better results when compared with other existing filter with PSNR value of 94%.","PeriodicalId":355617,"journal":{"name":"International Journal of Innovative Science and Research Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"De-Noising of Uterus Fibroid Ultrasound Image Using Gaussismooth Convolution Filter (GSCF)\",\"authors\":\"M. Devi, V. Sindhu\",\"doi\":\"10.38124/ijisrt20jul768\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper discusses the methods to detect the presence of uterus fibroid in woman by implementing various image processing techniques. The input image is an ultrasound image as it is cost effective when compared to other imaging techniques like CT, MRI. The initial step in image processing is to remove noise by applying filters. Application of filters smoothen the image without blurring the image. Gradient of the processed image is calculated and the image is enhanced by sharpening the edges of the image are achieved by calculating the local maxima of the gradient. Then, the edges are decided by calculating the threshold value of the processed image. The proposed Gaussismooth Convolution Filter gives better results when compared with other existing filter with PSNR value of 94%.\",\"PeriodicalId\":355617,\"journal\":{\"name\":\"International Journal of Innovative Science and Research Technology\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-08-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Innovative Science and Research Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.38124/ijisrt20jul768\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Innovative Science and Research Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.38124/ijisrt20jul768","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
De-Noising of Uterus Fibroid Ultrasound Image Using Gaussismooth Convolution Filter (GSCF)
This paper discusses the methods to detect the presence of uterus fibroid in woman by implementing various image processing techniques. The input image is an ultrasound image as it is cost effective when compared to other imaging techniques like CT, MRI. The initial step in image processing is to remove noise by applying filters. Application of filters smoothen the image without blurring the image. Gradient of the processed image is calculated and the image is enhanced by sharpening the edges of the image are achieved by calculating the local maxima of the gradient. Then, the edges are decided by calculating the threshold value of the processed image. The proposed Gaussismooth Convolution Filter gives better results when compared with other existing filter with PSNR value of 94%.