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논문 기본 정보

자료유형
학술저널
저자정보
Doyoung Park (SUNY Old Westbury)
저널정보
한국정보기술학회 JOURNAL OF ADVANCED INFORMATION TECHNOLOGY AND CONVERGENCE Journal of Advanced Information Technology and Convergence Vol.9 No.1
발행연도
2019.7
수록면
89 - 102 (14page)
DOI
10.14801/jaitc.2019.9.1.89

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초록· 키워드

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Collagen can be used in building artificial skin replacements for treatment of burns and towards the reconstruction of bone as well as researching cell behavior and cellular interaction. The strength of collagen in connective tissue rests on the characteristics of collagen fibers. 3D confocal imaging of collagen fibers enables the characterization of their spatial distribution as related to their function. However, the image stacks acquired with confocal laser-scanning microscope does not clearly show the collagen architecture in 3D. Therefore, we developed a new method to reconstruct, visualize and characterize collagen fibers from fluorescence confocal images. First, we exploit the tensor voting framework to extract sparse reliable information about collagen structure in a 3D image and therefore denoise and filter the acquired image stack. We then propose to segment the collagen fibers by defining an energy term based on the Hessian matrix. This energy term is minimized by a min cut-max flow algorithm that allows adaptive regularization. We demonstrate the efficacy of our methods by visualizing reconstructed collagen from specific 3D image stack.

목차

Abstract
1. Introduction
2. Previous/Related work
3. Collagen description
4. Collagen segmentation
5. Results
6. Conclusion
References

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UCI(KEPA) : I410-ECN-0101-2019-004-000944900