{"title":"On 2.5D surface reconstruction of cell cultures","authors":"W. Smith, K. Lam, D. Collins, J. Richardson","doi":"10.1109/ISPA.2013.6703742","DOIUrl":null,"url":null,"abstract":"The domain of image processing for cell microscopy presents non-trivial challenges that must be addressed for consistent image quality. One such challenge concerns the loss of focus as a result of cellular processes, where cell objects may move or change their morphology and, as a result, lie outside of the depth-of-view of the lens. This paper presents two approaches to addressing this problem; namely, the multiscale and geometric methods of image depth estimation. These algorithms are applied to a z-stack of images acquired from a standard phase contrast microscope and a total internal reflection microscope. To assess the algorithms in terms of their scalability, 10×, 20×, and 60× lens objectives are used to offer increased spatial resolutions as well as corresponding improvements in image quality.","PeriodicalId":425029,"journal":{"name":"2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPA.2013.6703742","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The domain of image processing for cell microscopy presents non-trivial challenges that must be addressed for consistent image quality. One such challenge concerns the loss of focus as a result of cellular processes, where cell objects may move or change their morphology and, as a result, lie outside of the depth-of-view of the lens. This paper presents two approaches to addressing this problem; namely, the multiscale and geometric methods of image depth estimation. These algorithms are applied to a z-stack of images acquired from a standard phase contrast microscope and a total internal reflection microscope. To assess the algorithms in terms of their scalability, 10×, 20×, and 60× lens objectives are used to offer increased spatial resolutions as well as corresponding improvements in image quality.