研究目的
To develop a software tool for the early detection and prevention of Glaucoma by processing biomedical images to locate the most relevant parameters within images obtained from the back of the eye, focusing on the dimensions and proportions of the cup and the optical disc.
研究成果
The developed software tool enables the detection of Glaucoma by processing medical images of the human eye fundus, focusing on the cup/disc ratio and the ISNT rule. It serves as a support tool for specialists, reducing diagnosis time and aiding in the early detection of Glaucoma.
研究不足
The proposed algorithm is not a system error-free but serves as an auxiliary support tool. It requires further development to identify the optic nerve and nerve fibers for a more comprehensive analysis.
1:Experimental Design and Method Selection:
The algorithm automatically locates the cup and the optical disc using image processing techniques, including conversion to grayscale, binarization, and morphological operations like dilation and erosion.
2:Sample Selection and Data Sources:
Images of the fundus of the eye from the Clinic 'Santa Lucia' database.
3:List of Experimental Equipment and Materials:
Not specified.
4:Experimental Procedures and Operational Workflow:
The process involves converting the image to grayscale, applying a median filter to reduce noise, using morphological operations to identify the cup and disc, and applying the ISNT rule for classification.
5:Data Analysis Methods:
Calculation of the cup/disc ratio and application of the ISNT rule to classify the image as normal or with Glaucoma.
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