Multi-objective radiomics model for predicting distant failure in lung SBRT-Reference-Cited by-同舟云学术

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Multi-objective radiomics model for predicting distant failure in lung SBRT

Published:2017-05-08 Issue:11 Volume:62 Page:4460-4478
ISSN:0031-9155
Container-title:Physics in Medicine and Biology
language:
Short-container-title:Phys. Med. Biol.

Author:

Zhou Zhiguo,Folkert Michael,Iyengar Puneeth,Westover Kenneth,Zhang Yuanyuan,Choy Hak,Timmerman Robert,Jiang Steve,Wang Jing

Funder

US National Institutes of Health

American Cancer Society

Publisher

IOP Publishing

Subject

Radiology Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Link

http://stacks.iop.org/0031-9155/62/i=11/a=4460/pdf

Reference35 articles.

1. A Systematic Review of the Factors Affecting Accuracy of SUV Measurements

2. Selecting of the optimal feature subset and kernel parameters in digital modulation classification by using hybrid genetic algorithm–support vector machines: HGASVM

3. Joint segmentation of anatomical and functional images: Applications in quantification of lesions from PET, PET-CT, MRI-PET, and MRI-PET-CT images

4. Mean shift, mode seeking, and clustering

5. Fault Diagnosis of Power Transformers Using SVM/ANN with Clonal Selection Algorithm for Features and Kernel Parameters Selection

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