Abstract
According to reports, lung cancer is gradually becoming the first cancer that threatens human life. The early stage of lung cancer is in the form of pulmonary nodules. The key issue in computer-aided diagnosis of lung tumors is to correct and accelerate rapid segmentation of diseased tissue. Therefore, this paper proposes a robust fuzzy c-mean clustering algorithm for pulmonary nodules segmentation, which can effectively improve the adaptive degree of local domain pixels. Since the information of the domain pixels does not necessarily have a positive correlation with the central pixels, the reference mechanism of domain window pixel information needs to be redefined. The robust fuzzy c-means clustering algorithm redefines the grayscale of the spatial pixel points in the domain and selects different fuzzy factors according to the reference standard. Based on this, the weights of different fuzzy factors are updated according to the characteristics of pixel points and gray fluctuation in pixel domain. The experimental results show that this method is superior to other typical algorithms in the segmentation of pulmonary nodules.
Highlights
IntroductionLung cancer is one of the most malignant tumors with the fastest growth in morbidity and mortality and the greatest threat to population health and life.Over the past 50 years, many countries have reported significant increases in the morbidity and mortality of lung cancer.Released statistics by the National Cancer Center in 2015 shows that incidence of lung cancer is close to 17.09%,and men accounted for 70.3% , women accounted for 29.7%,and the mortality rate is as high as 21.68%,ranking first among various tumors[1].Lung cancer will become the biggest threat to human health.If patients with lung cancer in early get standardized surgical treatment,the 5-year survival rate is as high as 90%.In the stage I treatment of lung cancer,the 5-year survival rate of patients is 60%, but in stage II-IV treatment of lung cancer,the 5-year survival rate reduces to 5% from 40%[2].In order not to miss the best treatment period, you need to find it as early as possible and treat it as soon as possible
Pulmonary nodules are the most common form of early lung cancer.In order to improve the true positive rate of lung nodules, CT images are used for the auxiliary diagnosis of pulmonary nodules.At present, CT image data shows an explosive growth trend, which is bound to increase the workload of doctors, leading to missed diagnosis and misdiagnosis.Studies have shown that accurate and effective lung CT image segmentation can reduce the amount of calculation, improve the efficiency of the entire diagnostic system, reduce missed diagnosis and misdiagnosis, and play an important role in the process of lung disease and function evaluation [3]
In order to further improve the accuracy and robustness of Fuzzy C-means Clustering (FCM) image segmentation algorithm,this paper proposes a Robust Fuzzy C-mean Clustering algorithm to improve the local area pixel adaptive degree.The robust fuzzy c-means clustering algorithm re-specifies the grayscale values of the pixels in the domain space by grayscale,and selects different fuzzy factors by reference standard.Based on this, the weights of different fuzzy factors are adaptively updated according to the characteristics of pixel points and the gray level fluctuations in the pixel domain
Summary
Lung cancer is one of the most malignant tumors with the fastest growth in morbidity and mortality and the greatest threat to population health and life.Over the past 50 years, many countries have reported significant increases in the morbidity and mortality of lung cancer.Released statistics by the National Cancer Center in 2015 shows that incidence of lung cancer is close to 17.09%,and men accounted for 70.3% , women accounted for 29.7%,and the mortality rate is as high as 21.68%,ranking first among various tumors[1].Lung cancer will become the biggest threat to human health.If patients with lung cancer in early get standardized surgical treatment,the 5-year survival rate is as high as 90%.In the stage I treatment of lung cancer,the 5-year survival rate of patients is 60%, but in stage II-IV treatment of lung cancer,the 5-year survival rate reduces to 5% from 40%[2].In order not to miss the best treatment period, you need to find it as early as possible and treat it as soon as possible. In order to further improve the accuracy and robustness of FCM image segmentation algorithm,this paper proposes a Robust Fuzzy C-mean Clustering algorithm to improve the local area pixel adaptive degree.The robust fuzzy c-means clustering algorithm re-specifies the grayscale values of the pixels in the domain space by grayscale,and selects different fuzzy factors by reference standard.Based on this, the weights of different fuzzy factors are adaptively updated according to the characteristics of pixel points and the gray level fluctuations in the pixel domain
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
