Hearing state prediction apparatus and method based on diffusion tensor image

A hearing state prediction method based on a diffusion tensor image, comprising:

• obtaining a diffusion tensor image to be processed, wherein the diffusion tensor image comprises a diffusion-weighted image;
• generating a diffusion index image based on the diffusion-weighted image;
• performing feature extraction on the diffusion index image to obtain a first depth feature;
• performing segmentation on the diffusion index image to obtain multiple segmented regions;
• performing feature extraction on the multiple segmented regions to obtain a second depth feature;
• and
• inputting the first depth feature and the second depth feature to a first deep learning model to obtain a hearing state corresponding to the depth feature, and the first deep learning model is trained to determine the hearing state.

A hearing state prediction model training apparatus, comprising:

• an obtaining module, configured to obtain a diffusion tensor image sample and a preset hearing state corresponding to the diffusion tensor image sample, wherein the diffusion tensor image sample comprises a diffusion-weighted image;
• a first determining module, configured to generate a diffusion index image according to the diffusion-weighted image;
• a second determining module, configured to perform feature extraction on the diffusion index image to obtain a first depth feature;
• perform segmentation on the diffusion index image to obtain multiple segmented regions;
• perform feature extraction on the multiple segmented regions to obtain a second depth feature;
• and input the first depth feature and the second depth feature to a first deep learning model to obtain a hearing state corresponding to the depth feature, and the first deep learning model is trained to determine the hearing state;
• and
• generating module, configured to determine a consistency between the hearing state and the preset hearing state corresponding to the diffusion tensor image sample, when the consistency between the hearing state and the preset hearing state is greater than or equal to a preset threshold, generating a hearing state prediction model.

A training method for a hearing state prediction model, comprising:

• obtaining a diffusion tensor image sample and a preset hearing state corresponding to the diffusion tensor image sample, wherein the diffusion tensor image sample comprises a diffusion-weighted image;
• generating a diffusion index image according to the diffusion-weighted image;
• performing feature extraction on the diffusion index image to obtain a first depth feature;
• performing segmentation on the diffusion index image to obtain multiple segmented regions;
• performing feature extraction on the multiple segmented regions to obtain a second depth feature;
• and inputting the first depth feature and the second depth feature to a first deep learning model to obtain a hearing state corresponding to the depth feature, and the first deep learning model is trained to determine the hearing state;
• and
• determining a consistency between the hearing state and the preset hearing state corresponding to the diffusion tensor image sample, when the consistency between the hearing state and the preset hearing state is greater than or equal to the preset threshold, a hearing state prediction model is generated.