Image classification method, computer-readable storage medium, and computer device
AssigneeTencent Technology (Shenzhen) Company Limited
InventorsYifan Hu, Yefeng Zheng
Life of this patent
Estimating the term…
Abstract
A computer device obtains a plurality of medical images. The device generates a texture image based on image data of a region of interest in the medical images. The device extracts a local feature from the texture image using a first network model. The device extracts a global feature from the medical images using a second network model. The device fuses the extracted local feature and the extracted global feature to form a fused feature. The device performs image classification based on the fused feature.
Claims19
An image classification method, applicable to a computer device, the method comprising:
- obtaining a plurality of medical images;
- generating a texture image based on image data of a region of interest (ROI) in the medical images;
- extracting a local feature from the texture image using a first network model;
- extracting a global feature from the medical images using a second network model;
- fusing the extracted local feature and the extracted global feature to form a fused feature using a fully connected layer;
- performing convolution calculation on the fused feature;
- and
- performing image classification on the medical images based on a result obtained through the convolution calculation of the fused feature.
A computer device, comprising:
- one or more processors;
- and
- memory storing one or more programs, that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:
- obtaining a plurality of medical images;
- generating a texture image based on image data of a region of interest (ROI) in the medical images;
- extracting a local feature from the texture image using a first network model;
- extracting a global feature from the medical images using a second network model;
- fusing the extracted local feature and the extracted global feature to form a fused feature using a fully connected layer;
- Performing convolution calculation on the fused feature;
- and
- performing image classification on the medical images based on a result obtained through the convolution calculation of the fused feature.
A non-transitory computer readable storage medium storing instructions that, when executed by one or more processors of a computer device, cause the one or more processors to perform operations comprising:
- obtaining a plurality of medical images;
- generating a texture image based on image data of a region of interest (ROI) in the medical images;
- extracting a local feature from the texture image using a first network model;
- extracting a global feature from the medical images using a second network model;
- fusing the extracted local feature and the extracted global feature to form a fused feature using a fully connected layer;
- performing convolution calculation on the fused feature;
- and
- performing image classification on the medical images based on a result obtained through the convolution calculation of the fused feature.
Dependencies are inferred from the claim text.