Wei Yang, Su Zhang, Yazhu Chen, Yaqing Chen, Wenying Li, Hongtao Lu
{"title":"超声诊断乳腺肿瘤恶性风险评估中的有效形态措施","authors":"Wei Yang, Su Zhang, Yazhu Chen, Yaqing Chen, Wenying Li, Hongtao Lu","doi":"10.1109/IMSCCS.2008.11","DOIUrl":null,"url":null,"abstract":"Malignant and benign breast tumors have different shape characteristics associated with their growth ways on sonography. Through analyzing the tumor shape pattern on the clinical images and the experimental results, we find that the tumor shape can be characterized on three aspects: convexity, ellipticity, and symmetry. In this paper, the shape measures are quantified using the polygonal approximation, the fitting ellipse, and local area integral invariant of contour respectively. The performance of these shape measures is evaluated on a breast ultrasound image data of 87 cases (49 benign and 38 malignant). Two combined convexity measures, an elliptic compactness, and a new reflection symmetry measure from local area integral invariant among the shape measures are appropriate and effective for distinguishing malignant and benign tumors, and all of their area under ROC curve can reach 0.9. They are significantly different between benign and malignant tumors on sonography, and show potential for the malignant risk assessment.","PeriodicalId":122953,"journal":{"name":"2008 International Multi-symposiums on Computer and Computational Sciences","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Effective Shape Measures in Malignant Risk Assessment for Breast Tumor on Sonography\",\"authors\":\"Wei Yang, Su Zhang, Yazhu Chen, Yaqing Chen, Wenying Li, Hongtao Lu\",\"doi\":\"10.1109/IMSCCS.2008.11\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Malignant and benign breast tumors have different shape characteristics associated with their growth ways on sonography. Through analyzing the tumor shape pattern on the clinical images and the experimental results, we find that the tumor shape can be characterized on three aspects: convexity, ellipticity, and symmetry. In this paper, the shape measures are quantified using the polygonal approximation, the fitting ellipse, and local area integral invariant of contour respectively. The performance of these shape measures is evaluated on a breast ultrasound image data of 87 cases (49 benign and 38 malignant). Two combined convexity measures, an elliptic compactness, and a new reflection symmetry measure from local area integral invariant among the shape measures are appropriate and effective for distinguishing malignant and benign tumors, and all of their area under ROC curve can reach 0.9. They are significantly different between benign and malignant tumors on sonography, and show potential for the malignant risk assessment.\",\"PeriodicalId\":122953,\"journal\":{\"name\":\"2008 International Multi-symposiums on Computer and Computational Sciences\",\"volume\":\"65 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-10-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 International Multi-symposiums on Computer and Computational Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IMSCCS.2008.11\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Multi-symposiums on Computer and Computational Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMSCCS.2008.11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Effective Shape Measures in Malignant Risk Assessment for Breast Tumor on Sonography
Malignant and benign breast tumors have different shape characteristics associated with their growth ways on sonography. Through analyzing the tumor shape pattern on the clinical images and the experimental results, we find that the tumor shape can be characterized on three aspects: convexity, ellipticity, and symmetry. In this paper, the shape measures are quantified using the polygonal approximation, the fitting ellipse, and local area integral invariant of contour respectively. The performance of these shape measures is evaluated on a breast ultrasound image data of 87 cases (49 benign and 38 malignant). Two combined convexity measures, an elliptic compactness, and a new reflection symmetry measure from local area integral invariant among the shape measures are appropriate and effective for distinguishing malignant and benign tumors, and all of their area under ROC curve can reach 0.9. They are significantly different between benign and malignant tumors on sonography, and show potential for the malignant risk assessment.