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The Journal of Practical Medicine ; (24): 782-785, 2015.
Article Dans Chinois | WPRIM | ID: wpr-460677

Résumé

Objective To investigate the value of endoscopic ultrasonography (EUS) and abdominal CT (CT) in diagnosis of periampullary lesions and to make comparison between the two procedures. Methods The patients suspected of surrounding lesions of ampullary from 2009 to 2013 in our hospital were included in this study. All the patients received both EUS and abdominal CT. The accuracy rate of these two examination methods was compared. Results 151 patients were confirmed as surrounding lesions of ampullary, including choledocholithiasis, ampullary tumors, ampullary inflammation, tumors of the pancreatic head and pancreatic cysts. The accuracy rate of these diseases was 83.6%, 90.6%, 6.5%, 100.0%, and 100.0%for EUS;while was 52.2%, 56.3%, 43.5%, 91.3%, and 100.0%for abdominal CT. The tatal accuracy rate for diagnosing periampullary lesions by EUS was significantly higher than that by abdominal CT (84.1% vs. 59.6%). Conclusions Endoscopic ultrasonography has higher value in diagnosis of periampullary lesions, and its accurate rate was higher than that of abdominal CT.

2.
Journal of Biomedical Engineering ; (6): 403-408, 2013.
Article Dans Chinois | WPRIM | ID: wpr-234641

Résumé

This paper is aimed to fulfill a prototype system used to classify and retrieve retinal image automatically. With the content-based image retrieval (CBIR) technology, a method to represent the retinal characteristics mixing the fundus image color (gray) histogram with bright, dark region features and other local comprehensive information was proposed. The method uses kernel principal component analysis (KPCA) to further extract nonlinear features and dimensionality reduced. It also puts forward a measurement method using support vector machine (SVM) on KPCA weighted distance in similarity measure aspect. Testing 300 samples with this prototype system randomly, we obtained the total image number of wrong retrieved 32, and the retrieval rate 89.33%. It showed that the identification rate of the system for retinal image was high.


Sujets)
Humains , Algorithmes , Fond de l'oeil , Traitement d'image par ordinateur , Méthodes , Mémorisation et recherche des informations , Méthodes , Analyse numérique assistée par ordinateur , Ophtalmoscopie , Normes de référence , Reconnaissance automatique des formes , Méthodes , Rétine , Anatomopathologie , Vaisseaux rétiniens , Anatomopathologie
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