Quantization method for echo feature and ultrasonic device correcting method using echo feature quantization value

Abstract

The invention provides a quantization method for an echo feature and an ultrasonic device correcting method using an echo feature quantization value. The quantization method for an echo feature comprises: receiving an ultrasonic image including a plurality of pixels with gray-scale values; circling a region of interest in the ultrasonic image; collecting statistics on the gray-scale values of the pixels in the region of interest to obtain a mean and a standard difference; excluding the pixels of which the gray-scale values are smaller than the product of a first multiplying power value and the standard difference, and the pixels of which the gray-scale values are greater than the product of the sum of the mean and a second multiplying power value and the standard difference in the region of interest; averaging the gray-scale values of the remaining pixels in the region of interest to obtain an interest mean; circling a reference area not superposed with the region of interest in the ultrasonic image; averaging the gray-scale values of the remaining pixels in the reference area to obtain a reference mean; and calculating the difference between the interest mean and the reference mean to obtain an echo indicator.

Description

technical field [0001] The present invention relates to a quantization method of echo features, a quantization system, and a correction method for quantizing numerical values ​​using echo features, in particular to a quantization method for grayscale (ie, gray scale) ultrasonic echo features and an ultrasonic wave using echo features to quantify numerical values. Device Calibration Method. Background technique [0002] Ultrasonic images are commonly used clinical diagnostic images in modern medicine. The echo intensity of gray-scale ultrasound images can reflect the internal structure or composition information of tissues, and is one of the important clinical diagnostic indicators. However, the echogenic interpretation of gray-scale ultrasound images may have interpretation errors due to the influence of different image parameter settings, screen presentation, ambient lighting, or personal subjective judgments, resulting in variations in computer analysis and subsequent sta...

AI Technical Summary

Problems solved by technology

However, the echogenic interpretation of gray-scale ultrasound images may have interpretation errors due to the influence of different image parameter settings, screen presentation, ambient lighting, or personal subjective judgments, resulting in variations in computer analysis and subsequent statistical analysis and clinical interpretation. Difficulties

[0003] Even if the same lesion is picked up by different ultrasonic devices, it is easy to have different echogenicity

Images