S. Yousefi, N. Kehtarnavaz, M. Akins, K. Luby‐Phelps, M. Mahendroo
{"title":"Distinguishing different stages of mouse pregnancy using Second Harmonic Generation images","authors":"S. Yousefi, N. Kehtarnavaz, M. Akins, K. Luby‐Phelps, M. Mahendroo","doi":"10.1109/SSST.2010.5442801","DOIUrl":null,"url":null,"abstract":"This paper presents an image processing approach for distinguishing three pregnancy stages of mice using Second Harmonic Generation (SHG) microscopy images. Three classes of SHG images for day 6, day 12 and day 18 of the 19-day mouse gestation period are considered. A classification is performed based on morphological features previously used for such SHG images, wavelet-based texture features, and a combination of morphological and wavelet-based texture features. It is shown that the combination of the features provide a more effective mechanism for distinguishing the three stages of mouse pregnancy as compared to each separate set of features.","PeriodicalId":6463,"journal":{"name":"2010 42nd Southeastern Symposium on System Theory (SSST)","volume":"17 1","pages":"44-46"},"PeriodicalIF":0.0000,"publicationDate":"2010-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 42nd Southeastern Symposium on System Theory (SSST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSST.2010.5442801","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
This paper presents an image processing approach for distinguishing three pregnancy stages of mice using Second Harmonic Generation (SHG) microscopy images. Three classes of SHG images for day 6, day 12 and day 18 of the 19-day mouse gestation period are considered. A classification is performed based on morphological features previously used for such SHG images, wavelet-based texture features, and a combination of morphological and wavelet-based texture features. It is shown that the combination of the features provide a more effective mechanism for distinguishing the three stages of mouse pregnancy as compared to each separate set of features.