Plantar pressure image registration method based on deep learning

Abstract

The invention discloses a plantar pressure image registration method based on deep learning. According to the invention, a cascade convolutional neural network regression model is used to estimate the registration parameters of a plantar pressure image, the to-be-registered plantar pressure image uses a main shaft algorithm to obtain an initial registration parameter, and further the rotation angle of the to-be-registered image is reduced to a certain range, so that the subsequent secondary registration is facilitated. The designed cascade convolutional neural network framework is divided into a coarse adjustment network and a fine adjustment network, a source plantar pressure image is generated through different transformation parameters, and the generated data set is used for model training, and then the to-be-registered image is input into the trained coarse adjustment network model and the trained fine adjustment network model in sequence, and finally, the results outputted by the coarse adjustment network model and the fine adjustment network model are superposed and combined to obtain a final plantar pressure image registration parameter, so that the efficiency of optimizing the registration parameter is remarkably improved.

Description

technical field [0001] The invention relates to the technical field of image registration, in particular to a method for image registration of plantar pressure based on deep learning. Background technique [0002] Plantar pressure image registration is of great importance for statistical and biomechanical analysis. In addition to the general mechanics of human gait, plantar pressure distribution provides researchers and experts in the medical field with information about the structure and function of the foot. important information. Therefore, it is very helpful in diagnosing foot discomfort, developing shoes, and obtaining useful information for gait analysis. Plantar pressure distribution also enables comparison of extremity loads in injured and non-injured patients, pre- and post-traumatic or surgical states. In addition, it excels at comparing patients and controls and provides detailed information specific to each contact area. [0003] There are many different techn...

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to provide a plantar pressure image registration method based on deep learning. The present invention introduces the convolutional neural network into the image registration. Learning ability to learn robust features embedded in images for updating image registration parameters to achieve near-real-time plantar pressure image registration, thereby solving the problem of low accuracy and time-consuming existing plantar pressure image registration methods long technical issues

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