{"title":"利用几何特征识别卵巢超声图像中的卵泡","authors":"P. Hiremath, Jyothi R. Tegnoor","doi":"10.1109/ICBPE.2009.5384097","DOIUrl":null,"url":null,"abstract":"Knowledge about the status of the female reproductive system is important for fertility problems and age related family planning. The volume of these fertility requests in our emancipated society is steadily increasing. Transvaginal ultrasound imaging of the follicles in the ovary gives important information about the ovarian aging, i.e., number of follicles, size, position and response to hormonal stimulation. Manual analysis of many follicles is laborious and error-prone. In this paper, a new method for recognition of follicles in ultrasound images of ovaries is proposed. This fully automated recognition method is based on extraction of geometric features of follicles. The proposed technique is tested on ultrasonographic images of ovaries. The experimental results are compared with inferences drawn by medical expert and demonstrate the efficacy of the method.","PeriodicalId":384086,"journal":{"name":"2009 International Conference on Biomedical and Pharmaceutical Engineering","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":"{\"title\":\"Recognition of follicles in ultrasound images of ovaries using geometric features\",\"authors\":\"P. Hiremath, Jyothi R. Tegnoor\",\"doi\":\"10.1109/ICBPE.2009.5384097\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Knowledge about the status of the female reproductive system is important for fertility problems and age related family planning. The volume of these fertility requests in our emancipated society is steadily increasing. Transvaginal ultrasound imaging of the follicles in the ovary gives important information about the ovarian aging, i.e., number of follicles, size, position and response to hormonal stimulation. Manual analysis of many follicles is laborious and error-prone. In this paper, a new method for recognition of follicles in ultrasound images of ovaries is proposed. This fully automated recognition method is based on extraction of geometric features of follicles. The proposed technique is tested on ultrasonographic images of ovaries. The experimental results are compared with inferences drawn by medical expert and demonstrate the efficacy of the method.\",\"PeriodicalId\":384086,\"journal\":{\"name\":\"2009 International Conference on Biomedical and Pharmaceutical Engineering\",\"volume\":\"52 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"27\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Biomedical and Pharmaceutical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICBPE.2009.5384097\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Biomedical and Pharmaceutical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICBPE.2009.5384097","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Recognition of follicles in ultrasound images of ovaries using geometric features
Knowledge about the status of the female reproductive system is important for fertility problems and age related family planning. The volume of these fertility requests in our emancipated society is steadily increasing. Transvaginal ultrasound imaging of the follicles in the ovary gives important information about the ovarian aging, i.e., number of follicles, size, position and response to hormonal stimulation. Manual analysis of many follicles is laborious and error-prone. In this paper, a new method for recognition of follicles in ultrasound images of ovaries is proposed. This fully automated recognition method is based on extraction of geometric features of follicles. The proposed technique is tested on ultrasonographic images of ovaries. The experimental results are compared with inferences drawn by medical expert and demonstrate the efficacy of the method.