Radiomics and deep learning in lung cancer-Reference-Cited by-同舟云学术

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Radiomics and deep learning in lung cancer

Published:2020-05-04 Issue:10 Volume:196 Page:879-887
ISSN:0179-7158
Container-title:Strahlentherapie und Onkologie
language:en
Short-container-title:Strahlenther Onkol

Author:

Avanzo Michele,Stancanello Joseph,Pirrone Giovanni,Sartor Giovanna

Publisher

Springer Science and Business Media LLC

Subject

Oncology,Radiology Nuclear Medicine and imaging

Link

https://link.springer.com/content/pdf/10.1007/s00066-020-01625-9.pdf

Reference86 articles.

1. Siegel RL, Miller KD, Jemal A (2018) Cancer statistics, 2018. CA Cancer J Clin 68:7–30

2. Hawkins S, Wang H, Liu Y, Garcia A, Stringfield O, Krewer H et al (2016) Predicting malignant nodules from screening CT scans. J Thorac Oncol 11(12):2120–2128

3. Avanzo M, Stancanello J, El Naqa I (2017) Beyond imaging: The promise of radiomics. Phys Med 38:122-139

4. Castiglioni I, Gallivanone F, Soda P, et al (2019) AI-based applications in hybrid imaging: how to build smart and truly multi-parametric decision models for radiomics. Eur J Nucl Med Mol Imaging 46(13):2673–2699. https://doi.org/10.1007/s00259-019-04414-4

5. Hassani C, Varghese BA, Nieva J, Duddalwar V (2019) Radiomics in pulmonary lesion imaging. AJR Am J Roentgenol 212:497–504

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