M. J. Carreira, D. Cabello, A. Mosquera, M. G. Penedo
{"title":"基于区域和边缘信息的医学图像分割","authors":"M. J. Carreira, D. Cabello, A. Mosquera, M. G. Penedo","doi":"10.1109/IEMBS.1992.5762095","DOIUrl":null,"url":null,"abstract":"An important task in image understanding systems is the segmentation process. In this work, we present a low-level algorithm which integrates statistical and spatial information for segmenting chest X-ray images. The goal of this algorithm is to generate a reasonable number of regions in the image to make easier the high-level analysis towards obtaining a symbolic description of the image.","PeriodicalId":6457,"journal":{"name":"1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society","volume":"1 1","pages":"1909-1910"},"PeriodicalIF":0.0000,"publicationDate":"1992-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Medical images segmentation using region and edges information\",\"authors\":\"M. J. Carreira, D. Cabello, A. Mosquera, M. G. Penedo\",\"doi\":\"10.1109/IEMBS.1992.5762095\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An important task in image understanding systems is the segmentation process. In this work, we present a low-level algorithm which integrates statistical and spatial information for segmenting chest X-ray images. The goal of this algorithm is to generate a reasonable number of regions in the image to make easier the high-level analysis towards obtaining a symbolic description of the image.\",\"PeriodicalId\":6457,\"journal\":{\"name\":\"1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society\",\"volume\":\"1 1\",\"pages\":\"1909-1910\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEMBS.1992.5762095\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEMBS.1992.5762095","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Medical images segmentation using region and edges information
An important task in image understanding systems is the segmentation process. In this work, we present a low-level algorithm which integrates statistical and spatial information for segmenting chest X-ray images. The goal of this algorithm is to generate a reasonable number of regions in the image to make easier the high-level analysis towards obtaining a symbolic description of the image.
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