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The Global ETD Search service is a free service for researchers
to find electronic theses and dissertations. This service is
provided by the
Networked Digital Library of Theses and Dissertations.
Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
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Showing 1 to 2 of 2 (0.043 seconds)Spelling suggestions: "subject:"cell are""
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Average Cell Orientation, Eccentricity and Size Estimated from Tissue ImagesIles, Peter January 2005 (has links)
Five image processing algorithms are proposed to measure the average orientation, eccentricity and size of cells in images of biological tissue. These properties, which can be embodied by an elliptical 'composite cell', are crucial for biomechanical tissue models. To automatically determine these properties is challenging due to the diverse nature of the image data, with tremendous and unpredictable variability in illumination, cell pigmentation, cell shape and cell boundary visibility. One proposed algorithm estimates the composite cell properties directly from the input tissue image, while four others estimate the properties from frequency domain data. The accuracy and stability of the algorithms are quantitatively compared through application to a wide variety of real images. Based on these results, the best algorithm is selected.
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| 2 |
Average Cell Orientation, Eccentricity and Size Estimated from Tissue ImagesIles, Peter January 2005 (has links)
Five image processing algorithms are proposed to measure the average orientation, eccentricity and size of cells in images of biological tissue. These properties, which can be embodied by an elliptical 'composite cell', are crucial for biomechanical tissue models. To automatically determine these properties is challenging due to the diverse nature of the image data, with tremendous and unpredictable variability in illumination, cell pigmentation, cell shape and cell boundary visibility. One proposed algorithm estimates the composite cell properties directly from the input tissue image, while four others estimate the properties from frequency domain data. The accuracy and stability of the algorithms are quantitatively compared through application to a wide variety of real images. Based on these results, the best algorithm is selected.
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