Lung feature recognition method, device, computer equipment and storage medium

Abstract

The invention relates to the field of artificial intelligence, and discloses a lung feature recognition method, a device, computer equipment and a storage medium. The method comprises the steps of obtaining to-be-recognized data which comprises a to-be-recognized lung image and to-be-recognized lung text description; performing lung image feature extraction through the lung image recognition modelto generate a lung image feature vector and an image recognition result, and performing lung text feature extraction through the lung text recognition model to generate a lung text feature vector anda text recognition result; fusing the lung image feature vector and the lung text feature vector by using an attention mechanism through a lung fusion recognition model, and extracting image text fusion features for recognition to obtain a fusion recognition result; and obtaining a lung feature recognition result through voting. According to the invention, the lung features can be accurately recognized, and the recognition accuracy and reliability are improved. The method is suitable for the field of intelligent medical treatment, and can further promote the construction of intelligent cities.

Description

technical field [0001] The invention relates to the field of image classification of artificial intelligence, in particular to a lung feature recognition method, device, computer equipment and storage medium. Background technique [0002] Under the current medical system, the identification of lung features mainly relies on medical personnel to manually distinguish lung image information based on their own experience. Because the movement of lung tissue is uneven and complicated, the identification process not only requires medical personnel time and energy, and there is a risk of misjudgment. At the same time, only the lung image information is often identified in the identification process, and the main complaint information of the lung image information (text description for the lung image information) is not identified. It is easy to lose the information of lung tissue movement, resulting in low accuracy and low efficiency. Contents of the invention [0003] The inven...

AI Technical Summary

Problems solved by technology

[0002] Under the current medical system, the identification of lung features mainly relies on medical personnel to manually distinguish lung image information based on their own experience. Because the movement of lung tissue is uneven and complicated, the identification process not only requires medical personnel time and energy, and there is a risk of misjudgment. At the same time, only the lung image information is often identified in the identification process, and the main complaint information of the lung image information (text description for the lung image information) is not identified. It is easy to lose the information of lung tissue movement, resulting in low accuracy and low efficiency

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