Multi-modal medical image acquisition device based on deep learning

Abstract

The invention relates to the technical field of medical image acquisition devices, and discloses a multi-modal medical image acquisition device based on deep learning. The device comprises a bottom plate, when images are acquired, a patient stands in the middle of the bottom plate, a driving motor is controlled to enable two outer cylinders to be close to each other and buckled, image data can beacquired, acquisition is more convenient, the workload of medical staff is reduced, a rotating motor is controlled to operate, inner cylinders in the outer cylinders can rotate through transmission, amedical image acquisition device can rotate along with rotation of the inner cylinders, and therefore the images around the human body can be acquired, and the acquisition range is wider; and moreover, the medical image acquisition device can be controlled to ascend or descend through a lifting motor, through mutual cooperation of rotation and lifting of the medical image acquisition device, thehuman body images can be acquired in all directions, the acquisition efficiency is higher, the heights of the outer cylinders and the inner cylinders can be controlled through hydraulic rods so as toadapt to patients with different heights, and use is more convenient.

Description

technical field [0001] The invention relates to the technical field of medical image acquisition devices, in particular to a multi-modal medical image acquisition device based on deep learning. Background technique [0002] Deep learning is a new research direction in the field of machine learning, which is introduced into machine learning to make it closer to the original goal-artificial intelligence. Deep learning is to learn the internal laws and representation levels of sample data. The information obtained during the learning process is of great help to the interpretation of data such as text, images and sounds. Its ultimate goal is to enable machines to have the ability to analyze and learn like humans, and to be able to recognize data such as text, images, and sounds. At present, deep learning has achieved many achievements in the fields of search technology, data mining, machine translation, natural language processing, multimedia learning and medical equipment. ...

AI Technical Summary

Problems solved by technology

Although the above-mentioned patents realize the automatic identification of lesion areas in medical images and improve the identification efficiency to a certain extent, they do not improve the image acquisition efficiency, and there are still deficiencies.

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