| Full text | |
| Author(s): |
Total Authors: 3
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| Affiliation: | [1] Univ Sao Paulo, Inst Math & Comp Sci ICMC, BR-13566590 Sao Carlos, SP - Brazil
[2] Univ Calif Davis, Dept Comp Sci, Davis, CA 95616 - USA
Total Affiliations: 2
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| Document type: | Journal article |
| Source: | IEEE Transactions on Image Processing; v. 29, p. 809-818, 2020. |
| Web of Science Citations: | 0 |
| Abstract | |
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. (AU) | |
| FAPESP's process: | 18/06074-0 - Recuperação de Imagens por Conteúdo Utilizando Atenção Visual Seletiva |
| Grantee: | Oscar Alonso Cuadros Linares |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 12/24036-1 - 3D segmentation of the head for assessing bone changes applied to Odontology. |
| Grantee: | Oscar Alonso Cuadros Linares |
| Support Opportunities: | Scholarships in Brazil - Doctorate |