Keratoconus recognition method and device based on multi-dimensional feature fusion

Abstract

The invention discloses a keratoconus recognition method and device based on multi-dimensional feature fusion, and the method comprises the steps: 1), carrying out the data processing through a designed standardized flow through the multi-dimensional data of a single patient, carrying out the grading of keratoconus, and dividing the keratoconus into a normal keratoconus, a subclinical keratoconusand a keratoconus; 2) constructing a multi-dimensional model, carrying out feature fusion in various modes, connecting an SE module to carry out feature recombination, and then carrying out model training; 3) carrying out interpretability operation of category judgment by utilizing gradient back propagation, and outputting a visual image; (4) comparing influences of one-dimensional convolution andtwo-dimensional convolution on the keratoconus data model for special consideration of the c keratoconus data model, and (5) selecting the category where the maximum score in the three scores is located as the discriminated category through the designed model to obtain a good classification effect, and optimizing the problem that the conic cornea recognition effect is poor in practical application.

Description

technical field [0001] The invention belongs to the technical field of medical data processing, and in particular relates to a keratoconus recognition method and device based on multidimensional feature fusion. Background technique [0002] In recent years, deep learning technology has developed rapidly in all walks of life, and medical assistance combined with deep learning technology has become the goal and direction of more and more people's efforts. Keratoconus is a slowly developing eye disease. It is difficult to diagnose in the early stage (that is, subclinical keratoconus), and there are no obvious clinical manifestations. The course of the disease varies from person to person. Significant corneal dilatation, central thinning, protruding forward, and conical shape are present, and advanced keratoconus can be diagnosed with a variety of ophthalmic equipment. The key problem is that in the early stage of the disease, it is difficult to diagnose but can be corrected by...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a keratoconus recognition method and device based on multi-dimensional feature fusion to solve the problem of inaccurate prediction of keratoconus in practical applications

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