{"title":"基于形态学运算和模糊聚类的超声图像分割","authors":"Haihua Liu, C. Xie, Zhouhui Chen, Yi Lei","doi":"10.1109/DELTA.2006.78","DOIUrl":null,"url":null,"abstract":"This paper presents a system for segmentation of ultrasound images. The system consists of two parts: local contrast enhancement and segmentation. The scheme for enhancing local contrast of images without speckle noise emphasis based on multiscale morphology is presented in the system. The intensity values of the scale-specific features of the image extracted using multiscale transformation are modified so as to enhance local contrast and suppress noise. Then, a new algorithm, called an alternative fuzzy c-mean (AFCM), is used for segmentation of ultrasound image. The unsupervised segmentation algorithm can help further to reduce the ultrasound imaging noise effects originating from the structures. We demonstrate effectiveness of the system for ultrasound image segmentation in experiments.","PeriodicalId":439448,"journal":{"name":"Third IEEE International Workshop on Electronic Design, Test and Applications (DELTA'06)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Segmentation of ultrasound image based on morphological operation and fuzzy clustering\",\"authors\":\"Haihua Liu, C. Xie, Zhouhui Chen, Yi Lei\",\"doi\":\"10.1109/DELTA.2006.78\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a system for segmentation of ultrasound images. The system consists of two parts: local contrast enhancement and segmentation. The scheme for enhancing local contrast of images without speckle noise emphasis based on multiscale morphology is presented in the system. The intensity values of the scale-specific features of the image extracted using multiscale transformation are modified so as to enhance local contrast and suppress noise. Then, a new algorithm, called an alternative fuzzy c-mean (AFCM), is used for segmentation of ultrasound image. The unsupervised segmentation algorithm can help further to reduce the ultrasound imaging noise effects originating from the structures. We demonstrate effectiveness of the system for ultrasound image segmentation in experiments.\",\"PeriodicalId\":439448,\"journal\":{\"name\":\"Third IEEE International Workshop on Electronic Design, Test and Applications (DELTA'06)\",\"volume\":\"95 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-01-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Third IEEE International Workshop on Electronic Design, Test and Applications (DELTA'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DELTA.2006.78\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Third IEEE International Workshop on Electronic Design, Test and Applications (DELTA'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DELTA.2006.78","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Segmentation of ultrasound image based on morphological operation and fuzzy clustering
This paper presents a system for segmentation of ultrasound images. The system consists of two parts: local contrast enhancement and segmentation. The scheme for enhancing local contrast of images without speckle noise emphasis based on multiscale morphology is presented in the system. The intensity values of the scale-specific features of the image extracted using multiscale transformation are modified so as to enhance local contrast and suppress noise. Then, a new algorithm, called an alternative fuzzy c-mean (AFCM), is used for segmentation of ultrasound image. The unsupervised segmentation algorithm can help further to reduce the ultrasound imaging noise effects originating from the structures. We demonstrate effectiveness of the system for ultrasound image segmentation in experiments.