{"title":"基于拉普拉斯混合偏微分方程的医学诊断超声图像去斑","authors":"S. Kalaivani Narayanan1, R. Wahidabanu","doi":"10.1109/ICCCCT.2010.5670608","DOIUrl":null,"url":null,"abstract":"In this paper, we propose an efficient noise reduction method that can be used to reduce speckle and jointly enhancing the edge information, rather than just inhibiting smoothing. In this method speckle is removed by filtering of band pass ultrasound images in Laplacian pyramid domain by using mixed PDE based nonlinear diffusion. In each pyramid layer, a gradient threshold is estimated automatically using robust median estimator. The mean absolute error (MAE) between two adjacent diffusion steps is used as stopping criterion. Quantitative results on synthetic data and simulated phantom show the performance of the proposed method compared to state of the art methods. Results on real images demonstrate that the proposed method is able to preserve edges & structural details of the image.","PeriodicalId":250834,"journal":{"name":"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES","volume":"55 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Despeckling of medical diagonostic ultrasound images via Laplacian based mixed PDE\",\"authors\":\"S. Kalaivani Narayanan1, R. Wahidabanu\",\"doi\":\"10.1109/ICCCCT.2010.5670608\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose an efficient noise reduction method that can be used to reduce speckle and jointly enhancing the edge information, rather than just inhibiting smoothing. In this method speckle is removed by filtering of band pass ultrasound images in Laplacian pyramid domain by using mixed PDE based nonlinear diffusion. In each pyramid layer, a gradient threshold is estimated automatically using robust median estimator. The mean absolute error (MAE) between two adjacent diffusion steps is used as stopping criterion. Quantitative results on synthetic data and simulated phantom show the performance of the proposed method compared to state of the art methods. Results on real images demonstrate that the proposed method is able to preserve edges & structural details of the image.\",\"PeriodicalId\":250834,\"journal\":{\"name\":\"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES\",\"volume\":\"55 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCCT.2010.5670608\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCCT.2010.5670608","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Despeckling of medical diagonostic ultrasound images via Laplacian based mixed PDE
In this paper, we propose an efficient noise reduction method that can be used to reduce speckle and jointly enhancing the edge information, rather than just inhibiting smoothing. In this method speckle is removed by filtering of band pass ultrasound images in Laplacian pyramid domain by using mixed PDE based nonlinear diffusion. In each pyramid layer, a gradient threshold is estimated automatically using robust median estimator. The mean absolute error (MAE) between two adjacent diffusion steps is used as stopping criterion. Quantitative results on synthetic data and simulated phantom show the performance of the proposed method compared to state of the art methods. Results on real images demonstrate that the proposed method is able to preserve edges & structural details of the image.