A pulmonary nodule image feature detection method based on a CT image

Abstract

The invention provides a pulmonary nodule image feature detection method based on a CT image, and the method mainly comprises the steps of carrying out the translation scanning of a pulmonary region,and automatically positioning all suspected pulmonary nodule image regions; based on the suspected areas, measuring the long and short diameters and the volume of the pulmonary nodules automatically with the coordinates of the center point as the sphere center and multiple scales as the diameter ranges; and then, filtering the CT value of the input image, automatically measuring the average CT value of the pulmonary nodules, and finally obtaining the average CT value. According to the invention, the functions of automatic positioning of pulmonary nodules, automatic measurement of long and short diameters and volumes, automatic measurement of CT average values and the like can be realized. Various image features of the pulmonary nodules automatically obtained through the detection method can serve as judgment bases, and doctors are assisted in better diagnosing the benign and malignant degree and the invasion degree of the pulmonary nodules.

Description

technical field [0001] The invention relates to a medical image detection method based on artificial intelligence technology, in particular to a method for detecting features of pulmonary nodules based on CT images. The image detection results obtained by using the method can assist doctors in predicting the benign condition of pulmonary nodules. Malignancy and degree of invasion. Background technique [0002] At present, radiologists mostly diagnose CT pulmonary nodules based on the following characteristics, namely size, density, fat content in calcified form, shape, margin, location of lung segment, number of layers in the image, and recent changes. Limited by the subjective differences of doctors' judgment standards and the nonlinear characteristics of these features, it is difficult to use these nodule features or their combination to improve the specificity of CT pulmonary nodule imaging diagnosis with the naked eye. However, pulmonary nodules based on traditional pat...

AI Technical Summary

Problems solved by technology

However, pulmonary nodules based on traditional pattern recognition technology have the disadvantages of low accuracy and high false positives, making it difficult to be used in actual clinical procedures

Images