R. Mammone, L. Barinov, A. Jairaj, W. Hulbert, C. Podilchuk
{"title":"利用压缩重采样和瞬时信噪比的医学超声斑点减少","authors":"R. Mammone, L. Barinov, A. Jairaj, W. Hulbert, C. Podilchuk","doi":"10.1109/SPMB.2013.6736769","DOIUrl":null,"url":null,"abstract":"Medical Ultrasonography is a valuable imaging technology for medical diagnostics and to guide interventional procedures. However, ultrasound imaging suffers from speckle noise, an inherent characteristic of all coherent imaging techniques due to the presence of sub-resolution scatterers. Speckle noise produces a reduction in contrast resolution which is responsible for the overall lower effective resolution of ultrasound compared to x-ray or MRI imaging. In the case of breast imaging, ultrasound speckle can mask small details such as low contrast tumors or microcalcifications, which may be an early indication of breast cancer. This limitation prevents ultrasound from displacing mammography as the gold standard for breast cancer screening. Traditional speckle reduction techniques attempt to remove speckle noise while preserving edges and other important features but there is always a tradeoff between removing the speckle noise and blurring tissue structure and details. We introduce a novel speckle reduction and contrast enhancement method for ultrasound imaging that is motivated by the fundamental ideas behind compressive sampling. We also introduce a way to estimate instantaneous SNR in order to identify the areas that are mostly signal from the areas that are mostly noise in order to preserve the signal while suppressing the noise. We have shown improvements in SNR on the order of 12dB in the lab and improved visualization of clinical data.","PeriodicalId":182231,"journal":{"name":"2013 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Speckle reduction of medical ultrasound using Compressive Re-Sampling and instantaneous SNR\",\"authors\":\"R. Mammone, L. Barinov, A. Jairaj, W. Hulbert, C. Podilchuk\",\"doi\":\"10.1109/SPMB.2013.6736769\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Medical Ultrasonography is a valuable imaging technology for medical diagnostics and to guide interventional procedures. However, ultrasound imaging suffers from speckle noise, an inherent characteristic of all coherent imaging techniques due to the presence of sub-resolution scatterers. Speckle noise produces a reduction in contrast resolution which is responsible for the overall lower effective resolution of ultrasound compared to x-ray or MRI imaging. In the case of breast imaging, ultrasound speckle can mask small details such as low contrast tumors or microcalcifications, which may be an early indication of breast cancer. This limitation prevents ultrasound from displacing mammography as the gold standard for breast cancer screening. Traditional speckle reduction techniques attempt to remove speckle noise while preserving edges and other important features but there is always a tradeoff between removing the speckle noise and blurring tissue structure and details. We introduce a novel speckle reduction and contrast enhancement method for ultrasound imaging that is motivated by the fundamental ideas behind compressive sampling. We also introduce a way to estimate instantaneous SNR in order to identify the areas that are mostly signal from the areas that are mostly noise in order to preserve the signal while suppressing the noise. We have shown improvements in SNR on the order of 12dB in the lab and improved visualization of clinical data.\",\"PeriodicalId\":182231,\"journal\":{\"name\":\"2013 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPMB.2013.6736769\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPMB.2013.6736769","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Speckle reduction of medical ultrasound using Compressive Re-Sampling and instantaneous SNR
Medical Ultrasonography is a valuable imaging technology for medical diagnostics and to guide interventional procedures. However, ultrasound imaging suffers from speckle noise, an inherent characteristic of all coherent imaging techniques due to the presence of sub-resolution scatterers. Speckle noise produces a reduction in contrast resolution which is responsible for the overall lower effective resolution of ultrasound compared to x-ray or MRI imaging. In the case of breast imaging, ultrasound speckle can mask small details such as low contrast tumors or microcalcifications, which may be an early indication of breast cancer. This limitation prevents ultrasound from displacing mammography as the gold standard for breast cancer screening. Traditional speckle reduction techniques attempt to remove speckle noise while preserving edges and other important features but there is always a tradeoff between removing the speckle noise and blurring tissue structure and details. We introduce a novel speckle reduction and contrast enhancement method for ultrasound imaging that is motivated by the fundamental ideas behind compressive sampling. We also introduce a way to estimate instantaneous SNR in order to identify the areas that are mostly signal from the areas that are mostly noise in order to preserve the signal while suppressing the noise. We have shown improvements in SNR on the order of 12dB in the lab and improved visualization of clinical data.