Lung nodule classification using local kernel regression models with out-of-sample extension-Reference-Cited by-同舟云学术

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Lung nodule classification using local kernel regression models with out-of-sample extension

Published:2018-02 Issue: Volume:40 Page:1-9
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Wei Guohui,Ma He,Qian Wei,Han Fangfang,Jiang Hongyang,Qi Shouliang,Qiu Min

Funder

Recruitment Program of Global Experts

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Bureau of Science and Technology of Liaoning Province

Publisher

Elsevier BV

Subject

Health Informatics,Signal Processing

Reference33 articles.

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2. Angiogenesis in non-small cell lung cancer: imaging with perfusion computed tomography;Ng;J. Thorac. Imaging,2010

3. Effects of guided random sampling of TCCs on blood flow values in CT perfusion studies of lung tumors;Gibaldi;Acad. Radiol.,2015

4. Computer-aided diagnosis for classifying benign versus malignant thyroid nodules based on ultrasound images: a comparison with radiologist-based assessments;Chang;Med. Phys.,2016

5. Computer-aided diagnosis of pulmonary nodules on CT scans: improvement of classification performance with nodule surface features;Way;Med. Phys.,2009

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