Pulmonary nodule detection method based on machine learning

Abstract

The invention discloses a pulmonary nodule detection method based on machine learning so that pulmonary nodule detection can be carried out automatically and the high precision can be kept. The methodcomprises: acquiring a CT image of a lung; segmenting the CT image to obtain a pulmonary parenchyma image; segmenting the pulmonary parenchyma image to obtain a plurality of pulmonary nodule candidates; extracting grayscale, shape and texture features of the pulmonary nodule candidates; and carrying out dimension reduction on multi-dimensional mixed features and carrying out classification by using a classifier with rules and support vector machine mixture to realize a pulmonary nodule detection effect. With the novel segmentation method and classification method, the false positive phenomenon is reduced and the detection precision of the pulmonary nodule of the medical image is improved. The pulmonary nodule detection method can be applied to the computer aided detection system.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to a method for detecting pulmonary nodules in medical images based on machine learning. Background technique [0002] Lung cancer ranks first in the incidence of malignant tumors in China, and the mortality rate has increased by 465% in the past 30 years. The average 5-year survival rate for early-stage lung cancer is between 55% and 70%. Therefore, early detection and treatment can greatly improve the cure rate of lung cancer. Lung cancer is always manifested as pulmonary nodules, and the lesion characteristics of lung lesions can be deduced according to the lesion characteristics of pulmonary nodules. Therefore, early detection and treatment of pulmonary nodules in patients with lung diseases is a key measure to reduce lung cancer mortality. Combined with the medical characteristics of pulmonary nodules, the use of computer-aided detection system (CAD) technology to p...

AI Technical Summary

Problems solved by technology

In the classification and identification of pulmonary nodules, it is usually obtained based on statistics, which requires prior knowledge or different feature attempts and parameter selection to obtain satisfactory features, which brings complexity to the entire classification problem and leads to existing medical problems. Detection of lung nodules in images is slow and less accurate

Images