Objective： To explore the role of the texture features of images in the diagnosis of solitary pulmonary nodules （SPNs） in different sizes. Materials and methods： A total of 379 patients with pathologically confirm...Objective： To explore the role of the texture features of images in the diagnosis of solitary pulmonary nodules （SPNs） in different sizes. Materials and methods： A total of 379 patients with pathologically confirmed SPNs were enrolled in this study. They were divided into three groups based on the SPN sizes： ≤10, 11-20, and 〉20 mm. Their texture features were segmented and extracted. The differences in the image features between benign and malignant SPNs were compared. The SPNs in these three groups were determined and analyzed with the texture features of images. Results： These 379 SPNs were successfully segmented using the 2D Otsu threshold method and the self-adaptive threshold segmentation method. The texture features of these SPNs were obtained using the method of grey level co-occurrence matrix （GLCM）. Of these 379 patients, 120 had benign SPNs and 259 had malignant SPNs. The entropy, contrast, energy, homogeneity, and correlation were 3.5597±0.6470, 0.5384±0.2561, 0.1921±0.1256, 0.8281±0.0604, and 0.8748±0.0740 in the benign SPNs and 3.8007±0.6235, 0.6088±0.2961, 0.1673±0.1070, 0.7980±0.0555, and 0.8550±0.0869 in the malignant SPNs （all P〈0.05）. The sensitivity, specificity, and accuracy of the texture features of images were 83.3%, 90.0%, and 86.8%, respectively, for SPNs sized 〈10 mm, and were 86.6%, 88.2%, and 87.1%, respectively, for SPNs sized 11-20 mm and 94.7%, 91.8%, and 93.9%, respectively, for SPNs sized 〉20 mm. Conclusions： The entropy and contrast of malignant pulmonary nodules have been demonstrated to be higher in comparison to those of benign pulmonary nodules, while the energy, homogeneity correlation of malignant pulmonary nodules are lower than those of benign pulmonary nodules. The texture features of images can reflect the tissue features and have high sensitivity, specificity, and accuracy in differentiating SPNs. The sensitivity and accuracy increase for larger SPNs.展开更多
A favorable tourism image of high-quality mountain scenic spots(HQMSS)is crucial for tourism prosperity and sustainability.This paper establishes a framework for investigating the tourism image based on cognitive-emot...A favorable tourism image of high-quality mountain scenic spots(HQMSS)is crucial for tourism prosperity and sustainability.This paper establishes a framework for investigating the tourism image based on cognitive-emotion theory and uses natural language processing(NLP)tools to clarify the cognition,emotion,and overall tourist image of the HQMSS in China from the perspective of tourist perception.This paper examines the multi-dimensional spatial differentiation of China's overall image,including province,scenic spot scales,as well as the spatial pattern of the overall comprehensive tourism image.Strategies for comprehensively improving HQMSS's tourism image are also formulated.The results show that:(1)The cognitive image of Chinese HQMSS is categorized into core and marginal images,and the core images such as scenery and cable car are the expression of the uniqueness of mountainous scenic spots.Additionally,the cognitive image is classified into six dimensions:tourism environment,tourism supporting facilities,tourism experience,tourism price,tourism service,and tourism safety.(2)Positive emotions are the dominant mood type of HQMSS in China,followed by neutral emotions,with negative emotions being the least frequent.Emotional images vary across dimensions,with tourism environment and tourism experience evoking relatively higher emotion.(3)The spatial pattern of HQMSS for each dimension at the national,provincial,and scenic scales is diversifying.This article provides a multidimensional perspective for investigating the tourism image of mountainous scenic spots,proposes targeted recommendations to improve the overall image of HQMSS in China,and can greatly contribute to the sustainable development of mountain tourism.展开更多
基金supported by National Natural Science Fund project [81202284]Guangdong Provincial Natural Science Fund project [S2011040004735]+2 种基金Project for Outstanding Young Innovative Talents in Colleges and Universities of Guangdong Province [LYM11106]Special Research Fund for Basic Scientific Research Projects in Central Universities [21612305, 21612101]Guangzhou Municipal Science and Technology Fund project [2014J4100119]
文摘Objective： To explore the role of the texture features of images in the diagnosis of solitary pulmonary nodules （SPNs） in different sizes. Materials and methods： A total of 379 patients with pathologically confirmed SPNs were enrolled in this study. They were divided into three groups based on the SPN sizes： ≤10, 11-20, and 〉20 mm. Their texture features were segmented and extracted. The differences in the image features between benign and malignant SPNs were compared. The SPNs in these three groups were determined and analyzed with the texture features of images. Results： These 379 SPNs were successfully segmented using the 2D Otsu threshold method and the self-adaptive threshold segmentation method. The texture features of these SPNs were obtained using the method of grey level co-occurrence matrix （GLCM）. Of these 379 patients, 120 had benign SPNs and 259 had malignant SPNs. The entropy, contrast, energy, homogeneity, and correlation were 3.5597±0.6470, 0.5384±0.2561, 0.1921±0.1256, 0.8281±0.0604, and 0.8748±0.0740 in the benign SPNs and 3.8007±0.6235, 0.6088±0.2961, 0.1673±0.1070, 0.7980±0.0555, and 0.8550±0.0869 in the malignant SPNs （all P〈0.05）. The sensitivity, specificity, and accuracy of the texture features of images were 83.3%, 90.0%, and 86.8%, respectively, for SPNs sized 〈10 mm, and were 86.6%, 88.2%, and 87.1%, respectively, for SPNs sized 11-20 mm and 94.7%, 91.8%, and 93.9%, respectively, for SPNs sized 〉20 mm. Conclusions： The entropy and contrast of malignant pulmonary nodules have been demonstrated to be higher in comparison to those of benign pulmonary nodules, while the energy, homogeneity correlation of malignant pulmonary nodules are lower than those of benign pulmonary nodules. The texture features of images can reflect the tissue features and have high sensitivity, specificity, and accuracy in differentiating SPNs. The sensitivity and accuracy increase for larger SPNs.
基金supported by Natural Science Foundation of Heilongjiang Province,China[LH2019D009]。
文摘A favorable tourism image of high-quality mountain scenic spots(HQMSS)is crucial for tourism prosperity and sustainability.This paper establishes a framework for investigating the tourism image based on cognitive-emotion theory and uses natural language processing(NLP)tools to clarify the cognition,emotion,and overall tourist image of the HQMSS in China from the perspective of tourist perception.This paper examines the multi-dimensional spatial differentiation of China's overall image,including province,scenic spot scales,as well as the spatial pattern of the overall comprehensive tourism image.Strategies for comprehensively improving HQMSS's tourism image are also formulated.The results show that:(1)The cognitive image of Chinese HQMSS is categorized into core and marginal images,and the core images such as scenery and cable car are the expression of the uniqueness of mountainous scenic spots.Additionally,the cognitive image is classified into six dimensions:tourism environment,tourism supporting facilities,tourism experience,tourism price,tourism service,and tourism safety.(2)Positive emotions are the dominant mood type of HQMSS in China,followed by neutral emotions,with negative emotions being the least frequent.Emotional images vary across dimensions,with tourism environment and tourism experience evoking relatively higher emotion.(3)The spatial pattern of HQMSS for each dimension at the national,provincial,and scenic scales is diversifying.This article provides a multidimensional perspective for investigating the tourism image of mountainous scenic spots,proposes targeted recommendations to improve the overall image of HQMSS in China,and can greatly contribute to the sustainable development of mountain tourism.
