Laxman Singh, Z. Jaffery, Z. Zaheeruddin, R. Singh
{"title":"乳腺肿瘤在乳房x光片上的分割与表征","authors":"Laxman Singh, Z. Jaffery, Z. Zaheeruddin, R. Singh","doi":"10.1109/ARTCOM.2010.60","DOIUrl":null,"url":null,"abstract":"The objective of this paper is to present a novel approach for the segmentation and characterization of breast tumor. The authors have developed an efficient tumor segmentation technique using conventional Ostu thresholding method aided by morphological reconstruction filtering technique. The parameters extracted are area, major and minor axis length, eccentricity, solidity, average gray level, standard deviation, and entropy. This method is simple, fast and versatile. This can be applied for the segmentation of all types of breast tumor irrespective of their size. The proposed technique has been implemented on MATLAB 7.3 and results are compared with the existing techniques such as standard Ostu thresholding method and region growing method proposed by Zucker. The simulated result shows that the performance of the proposed technique is better than that of existing techniques.","PeriodicalId":398854,"journal":{"name":"2010 International Conference on Advances in Recent Technologies in Communication and Computing","volume":"2004 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Segmentation and Characterization of Breast Tumor in Mammograms\",\"authors\":\"Laxman Singh, Z. Jaffery, Z. Zaheeruddin, R. Singh\",\"doi\":\"10.1109/ARTCOM.2010.60\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The objective of this paper is to present a novel approach for the segmentation and characterization of breast tumor. The authors have developed an efficient tumor segmentation technique using conventional Ostu thresholding method aided by morphological reconstruction filtering technique. The parameters extracted are area, major and minor axis length, eccentricity, solidity, average gray level, standard deviation, and entropy. This method is simple, fast and versatile. This can be applied for the segmentation of all types of breast tumor irrespective of their size. The proposed technique has been implemented on MATLAB 7.3 and results are compared with the existing techniques such as standard Ostu thresholding method and region growing method proposed by Zucker. The simulated result shows that the performance of the proposed technique is better than that of existing techniques.\",\"PeriodicalId\":398854,\"journal\":{\"name\":\"2010 International Conference on Advances in Recent Technologies in Communication and Computing\",\"volume\":\"2004 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Advances in Recent Technologies in Communication and Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ARTCOM.2010.60\",\"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 Advances in Recent Technologies in Communication and Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ARTCOM.2010.60","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Segmentation and Characterization of Breast Tumor in Mammograms
The objective of this paper is to present a novel approach for the segmentation and characterization of breast tumor. The authors have developed an efficient tumor segmentation technique using conventional Ostu thresholding method aided by morphological reconstruction filtering technique. The parameters extracted are area, major and minor axis length, eccentricity, solidity, average gray level, standard deviation, and entropy. This method is simple, fast and versatile. This can be applied for the segmentation of all types of breast tumor irrespective of their size. The proposed technique has been implemented on MATLAB 7.3 and results are compared with the existing techniques such as standard Ostu thresholding method and region growing method proposed by Zucker. The simulated result shows that the performance of the proposed technique is better than that of existing techniques.