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Isolation of Intact Eyeball to Obtain Integral Ocular Surface Tissue for Histological Examination and Immunohistochemistry

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Published on: October 20, 2019

[The segmentation of eye socket].

Yun Zhu¹, Jie Yang, Zhiqiang Yu

¹Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai 200030, China. yunzhu@sjtu.edu.cn

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi = Journal of Biomedical Engineering = Shengwu Yixue Gongchengxue Zazhi

|November 22, 2005

Summary

We developed a hybrid level set model for accurate eye socket segmentation. This robust method improves 3-D reconstruction and implant calculations for computer-aided surgery.

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Area of Science:

Medical image analysis
Computer-aided surgery

Background:

Accurate segmentation of anatomical structures is crucial for medical applications.
Existing level set methods face challenges like the 'leaking problem', limiting their accuracy.

Purpose of the Study:

To introduce a novel hybrid level set model for enhanced eye socket segmentation.
To address the limitations of traditional boundary-based level set methods.

Main Methods:

A hybrid level set model integrating region and boundary information was developed.
The model was applied to segment the eye socket in medical images.

Main Results:

The hybrid model demonstrated superior robustness and accuracy compared to other level set methods.
The segmentation results effectively solved the leaking problem inherent in boundary-based approaches.

Conclusions:

The proposed hybrid level set model offers a significant improvement for eye socket segmentation.
This technique facilitates precise 3-D eye socket reconstruction and hydroxyapatite implant calculations in computer-aided surgery.