Patent ID: 11954852
Assignee: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED
Field: Medical technology (Instruments)
Classification: CPC G | IPC G

Claim 10:
11. A non-transitory computer-readable storage medium, storing computer-readable instructions, wherein, the computer-readable instructions, when executed by a processor, are configured to cause the processor to perform:
obtaining a medical image data set;
performing quality analysis on the medical image data set, to extract feature information of a medical image in the medical image data set, the quality analysis comprising at least one of the following: hue-saturation-lightness analysis, definition analysis, texture analysis, or entropy value analysis, by:
performing at least one of the following: the hue-saturation-lightness analysis, the definition analysis, the texture analysis, or the entropy value analysis on the medical image data set, to extract the feature information of the medical image, wherein the feature information comprises at least one of the following: hue feature information, saturation feature information, lightness feature information, a definition index, a grayscale edge, or an entropy value; and

classifying the medical image data set based on the feature information and by using a pre-trained deep learning network for performing anomaly detection and classification, to obtain a classification result,
wherein:
when the computer-readable instructions are configured to cause the processor to perform performing the hue-saturation-lightness analysis, the computer-readable instructions are configured to cause the processor to perform converting values of a red coordinate, a green coordinate, and a blue coordinate of the medical image from an RGB space to an HSV space, to obtain hue feature information, saturation feature information, and lightness feature information;
when the computer-readable instructions are configured to cause the processor to perform performing the definition analysis, the computer-readable instructions are configured to cause the processor to perform:
calculating a value of a digital image matrix of the medical image,
performing convolution on the value of the digital image matrix and a 5×5 Gaussian convolution kernel to obtain a convolution value, and
calculating a definition index of the medical image based on a minimum mean square error of the value of the digital image matrix and the convolution value;

when the computer-readable instructions are configured to cause the processor to perform performing the texture analysis, the computer-readable instructions are configured to cause the processor to perform extracting a grayscale edge of the medical image by using a Sobel verification operator; and
when the computer-readable instructions are configured to cause the processor to perform performing the entropy value analysis, the computer-readable instructions are configured to cause the processor to perform calculating an entropy value according to a length of the medical image, a width of the medical image, and a quantity of times and a probability that a grayscale value of a center pixel in a sliding window and an average of grayscale values other than that of the center pixel in the sliding window occur in the medical image.