Prediction of brain metastases from nonsmall cell lung cancer using multimodal radiomics and deep learning based on <sup>18</sup>FPET/CT images-Reference-Cited by-同舟云学术

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Prediction of brain metastases from nonsmall cell lung cancer using multimodal radiomics and deep learning based on ¹⁸FPET/CT images

Published:2023-11-04 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD)
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Author:

Huang Z.¹,Zhu Y.¹,Li W.¹,Yang L.¹,Yang Y.¹,Liang D.¹,Shao D.²,Hu Z.¹

Affiliation:

1. Chinese Academy of Sciences, Lauterbur Research Center for Biomedical Imaging,Shenzhen Institute of Advanced Technology,Shenzhen,China

2. Guangdong Academy of Medical Sciences,Guangdong Provincial People's Hospital,Department of Nuclear Medicine,Guangzhou,China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10337770/10337807/10338666.pdf?arnumber=10338666

Reference4 articles.

1. The Effect of Gefitinib on Treatment Necessity and Prognosis of NSCLC Patients with Early EGFR Mutations

2. Predicting survival after radiosurgery in patients with lung cancer brain metastases using deep learning of radiomics and EGFR status

3. Multimodality MRI-based radiomics approach to predict the posttreatment response of lung cancer brain metastases to gamma knife radiosurgery

4. A radiomics evaluation of 2D and 3D MRI texture features to classify brain metastases from lung cancer and melanoma

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