Mobile phone end vein imaging method based on deep learning

Abstract

The invention discloses a mobile phone end vein imaging method based on deep learning, and belongs to the technical field of image processing and deep learning. The method comprises the following steps: 1) vein image data set processing: acquiring synchronous skin visible light images and near-infrared images, enhancing the near-infrared images, highlighting vein information, and providing true value data for subsequent network training; 2) designing and training a vein imaging network: constructing the vein imaging network, and training the network by taking the processed vein image data set as a training set; 3) network weight reduction: improving a development network, and compressing the parameter scale and the calculation amount of the development network; and 4) mobile phone end deployment and application: deploying the lightweight network to the mobile phone end for operation, and realizing vein imaging of the mobile phone end. The invention improves the convenience of vein imaging work based on a deep learning method and a mobile phone end open source neural network reasoning framework, and has great use value in the medical field.

Description

technical field [0001] The invention relates to the technical field of image processing and deep learning, in particular to a method for imaging veins at a mobile phone terminal based on deep learning. Background technique [0002] In the medical field, venipuncture is an essential operation in today's medical treatment and nursing care, for clinical administration of fluids and blood transfusions. The premise of performing venipuncture is to determine the position of the vein, and usually experienced medical personnel determine the patient's vein position by eye observation and finger touch. Because the virus is highly contagious, medical staff must wear protective gloves, protective clothing and goggles when treating infected patients. Airtight protective clothing prevents the heat generated by the body from getting rid of, and the water vapor generated by breathing adheres to the inner surface of the goggles, which will greatly affect vision. At the same time, protective...

AI Technical Summary

Problems solved by technology

[0004] Aiming at the problems existing in the prior art, the present invention adopts a deep learning-based mobile phone vein imaging method, which is based on the deep learning method and the mobile phone open source neural network reasoning framework. This method overcomes the dependence of the existing vein imaging method on specific external devices , poor portability and high noise in imaging results

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