Auxiliary interpretation method and device based on artificial intelligence, terminal and storage medium
A technology of artificial intelligence and convolutional neural network, applied in the field of intelligent medical auxiliary interpretation, can solve problems such as limited effect
Pending Publication Date: 2020-10-27
NAT UNIV OF SINGAPORE +1
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Problems solved by technology
[0004] There have been some attempts and progress in using deep learning for intelligent assisted interpretation, but due to the characteristics of the field of medical interpretation, the assisted interpretation of artificial intelligence-based deep learning technology is often limited
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[0084] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.
[0085] In one embodiment, a terminal is provided, and application programs can be installed on the terminal. The terminal can be a mobile phone, a tablet computer, a notebook computer, a desktop computer, and the like. Such as figure 1 As shown, the terminal includes a processor connected through a system bus, an internal memory, a non-volatile storage medium, a network interface, a display screen and an input device. Among them, the processor is used to provide computing and control capabilities to support the operation of the entire terminal. The non-volatile storage ...
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The invention relates to an auxiliary interpretation method and device based on artificial intelligence, a terminal and a storage medium. The auxiliary interpretation method based on artificial intelligence comprises the following steps: initializing parameters of a first convolutional neural network, parameters of a second convolutional neural network and parameters of a GRU recurrent neural network; acquiring to-be-interpreted image information, and preprocessing the to-be-interpreted image information; performing preliminary processing by using a first convolutional neural network to obtaina preliminary feature vector of the to-be-interpreted image information and a classified to-be-interpreted image sequence; extracting Laplacian features and Hessian matrix features of the gray features, and processing the Laplacian features and the Hessian matrix features by using a second convolutional neural network to obtain Laplacian feature vectors and Hessian matrix feature vectors respectively; fusing the Laplacian eigenvector, the Hessian matrix eigenvector and the preliminary eigenvector to form a combined eigenvector, and processing the combined eigenvector by adopting a GRU recurrent neural network; and displaying the processing result for auxiliary interpretation, and storing the interpretation result.
Description
technical field [0001] The invention relates to the field of intelligent medical auxiliary interpretation, in particular to an artificial intelligence-based auxiliary interpretation method, device, terminal and storage medium. Background technique [0002] Some medical tools for visualization of internal organs of the human body can fully display the condition of human organs from the inside without the pain and discomfort of conventional endoscopy, and are very easy to implement. But the number and complexity of video images produced by these visualized medical tools can be very challenging for recognition. For example, video recordings of a patient's normal small intestine by a capsule endoscope can last up to 8 hours, and if 2 frames per second is used, a video can contain as many as 57,600 images (the number of images at 24 frames per second will reached 691,200); secondly, visualized medical tools may move freely in human organs, and the imaging conditions of the captu...
Claims
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Login to View More IPC IPC(8): G16H30/00G06K9/62G06N3/04
CPCG16H30/00G06N3/045G06F18/241G06F18/214
Inventor 郭永新郭英凯王博
Owner NAT UNIV OF SINGAPORE