The method and efficacy of support vector machine classifiers based on texture features and multi-resolution histogram from 18F-FDG PET-CT images for the evaluation of mediastinal lymph nodes in patients with lung cancer-Reference-Cited by-同舟云学术

The method and efficacy of support vector machine classifiers based on texture features and multi-resolution histogram from 18F-FDG PET-CT images for the evaluation of mediastinal lymph nodes in patients with lung cancer

Published:2015-02 Issue:2 Volume:84 Page:312-317
ISSN:0720-048X
Container-title:European Journal of Radiology
language:en
Short-container-title:European Journal of Radiology

Author:

Gao Xuan,Chu Chunyu,Li Yingci,Lu Peiou,Wang Wenzhi,Liu Wanyu,Yu Lijuan

Funder

National Natural Science Fund of China

Publisher

Elsevier BV

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Reference25 articles.

1. Diagnostic value of fluorine 18 fluorodeoxyglucose positron emission tomography/computed tomography for the detection of metastases in non-small-cell lung cancer patients;Wu;Int J Cancer,2013

2. The maximum standardized 18F-fluorodeoxyglucose uptake on positron emission tomography predicts lymph node metastasis and invasiveness in clinical stage IA non-small cell lung cancer;Maeda;Interact Cardiovasc Thorac Surg,2009

3. Prediction of true-negative lymph node metastasis in clinical IA non-small cell lung cancer by measuring standardized uptake values on positron emission tomography;Takenaka;Surg Today,2012

4. Increased standardized uptake value in the primary lesion predicts nodal or distant metastases at presentation in lung cancer;Sachs;Clin Lung Cancer,2005

5. Computer aided differential diagnosis of pulmonary nodules using curvature based analysis;Kawata,1999

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