Corneal nerve curvature measuring system and method based on IVCM image

Abstract

The invention discloses a corneal nerve curvature measuring system and method based on an IVCM image. The measurement system comprises an image acquisition and preprocessing module, a corneal nerve segmentation module, a nerve segmentation curvature calculation module, a polymerization parameter selection module, a nerve segmentation curvature polymerization module, an analysis result display module and the like. The system is different from an existing end-to-end model based on deep learning. A process that a doctor estimates the curvature grading of the whole image according to some representative nerve segments in the living body confocal microscope image is simulated; the curvature of each nerve segment in the living body confocal microscope is aggregated by adopting multiple parameter-adjustable functions, the solvability is high, the correlation with a doctor evaluation result is high, the doctor can directly adjust the aggregation parameters in combination with professional knowledge, the adjustment process is visual and transparent, the application in auxiliary clinical diagnosis is facilitated, and the practicability is high.

Description

technical field [0001] The present application relates to a method for measuring corneal nerve curvature, in particular to a corneal nerve curvature measurement system and method based on in vivo confocal microscopy (IVCM) images, and belongs to the field of computer technology. Background technique [0002] Intravital confocal microscopy enables rapid and non-invasive visualization of living corneal nerve fibers. Due to the unclear definition of the curvature of the corneal nerve, doctors need to rely on personal experience in diagnosis and treatment when evaluating the curvature of the corneal nerve. They can only roughly grade the curvature, and cannot obtain accurate values, and there will be different doctor grading results Inconsistent situations. [0003] In recent years, researchers in this field have proposed a variety of automatic corneal nerve image curvature calculation methods based on computer-aided image processing technology, such as the method of calculatin...

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Problems solved by technology

However, since multiple corneal nerve segments are included in an intravital confocal microscope image, none of the above methods can simulate the process by which physicians estimate the overall curvature of the corneal nerve in an image based on the curvature of multiple nerve segments in that image

Taking the curvature calculation based on geometry as an example, it mainly obtains the curvature representing the nerve in the whole image by arithmetically averaging the curvature of each nerve segment or weighting the average according to its length. Some representative nerve segments estimate the curvature grading of the entire image, and the curvature calculated by simple average or weighted average has low correlation with the doctor's evaluation results, which cannot assist doctors in clinical diagnosis

[0004] On the other hand, the existing automated methods for calculating the curvature of corneal nerve images generally only average the curvature of each nerve segment in an image or weight the average according to the length of each segment of corneal nerve to obtain a representative nerve in the entire image. Curvature, which is also far from the doctor's evaluation process

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