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|a 10.1109/TIP.2019.2936743
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|a eng
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| 100 |
1 |
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|a Linares, Oscar Cuadros
|e verfasserin
|4 aut
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| 245 |
1 |
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|a Segmenting Cellular Retinal Images by Optimizing Super-pixels, Multi-level Modularity, and Cell Boundary Representation
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|c 2019
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|a Text
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|a ƒaComputermedien
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|a ƒa Online-Ressource
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|a Date Revised 27.02.2024
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|a published: Print-Electronic
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|a Citation Status Publisher
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| 520 |
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|a We introduce an interactive method for retina layer segmentation in gray-level and RGB images based on super-pixels, multi-level optimization of modularity, and boundary erosion. Our method produces highly accurate segmentation results and can segment very large images. We have evaluated our method with two datasets of 2D confocal microscopy (CM) images of a mammalian retina.We have obtained average Jaccard index values of 0.948 and 0.942 respectively, confirming the high-quality segmentation performance of our method relative to a known ground truth segmentation. Average processing time was two seconds
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|a Journal Article
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|a Hamann, Bernd
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Neto, Joao Batista
|e verfasserin
|4 aut
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g (2019) vom: 27. Aug.
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|u http://dx.doi.org/10.1109/TIP.2019.2936743
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