Microcomputer Software Applied to Corneal Stromal Biometry

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Abstract
Here we report a new method for image analysis of the corneal stroma. To obtain the biometric characteristics of a given area, we perform three different treatments of the same image. These automated predictions closely match each parameter (length, surface area, etc.), as measured manually by a "blind investigator." Furthermore, to obtain quantifiable, average values, we have increased the number of successive image measurements, which has led to the development of a series of programs designed to optimize automated data handling. Finally, the acquired, calculated parameters are summarized in the form of intermediate tables for each series of images, and as a final summary table incorporating t-test values and permitting comparison between two stromas (e.g., normal and pathological). Multivariate analysis and an ascending hierarchical classification demonstrate the main trends in differences of pathological vs. normal stroma.

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