Efficient 3D texture feature extraction from CT images for computer-aided diagnosis of pulmonary nodules-Reference-Cited by-同舟云学术

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Efficient 3D texture feature extraction from CT images for computer-aided diagnosis of pulmonary nodules

Published:2014-03-18 Issue: Volume: Page:
ISSN:0277-786X
Container-title:SPIE Proceedings
language:
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Author:

Han Fangfang,Wang Huafeng,Song Bowen,Zhang Guopeng,Lu Hongbing,Moore William,Liang Zhengrong,Zhao Hong

Publisher

SPIE

Reference10 articles.

1. “Cancer Facts Figures 2012,” Atlanta: American Cancer Society, (2012).

2. Screening for Early Lung Cancer with Low-Dose Spiral CT: Prevalence in 817 Asymptomatic Smokers

3. Computer analysis of computed tomography scans of the lung: a survey

4. Comparison of Image Features Calculated in Different Dimensions for Computer-Aided Diagnosis of Lung Nodules;Xu,2009

5. A New 3D Texture Feature Based Computer-Aided Diagnosis Approach to Differentiate Pulmonary Nodules;Han,2013

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Predicting unnecessary nodule biopsy for a small lung cancer screening dataset by less-abstractive deep features;Medical Imaging 2019: Computer-Aided Diagnosis;2019-03-13

2. A hybrid CNN feature model for pulmonary nodule malignancy risk differentiation;Journal of X-Ray Science and Technology;2018-04-06

3. Risk prediction of small pulmonary nodules based on novel CT image texture markers;SPIE Proceedings;2017-03-03

4. A Hybrid CNN Feature Model for Pulmonary Nodule Differentiation Task;Imaging for Patient-Customized Simulations and Systems for Point-of-Care Ultrasound;2017

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