Optimizing the Size of Peritumoral Region for Assessing Non-Small Cell Lung Cancer Heterogeneity Using Radiomics
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Zhang, Xingping, Zhang, Guijuan, Qiu, Xingting, Yin, Jiao 
ORCID: 0000-0002-0269-2624, Tan, Wenjun, Yin, Xiaoxia, Yang, Hong, Wang, Kun and Zhang, Yanchun ORCID: 0000-0002-5094-5980
(2023)
Optimizing the Size of Peritumoral Region for Assessing Non-Small Cell Lung Cancer Heterogeneity Using Radiomics.
In:
Health Information Science: 12th International Conference, HIS 2023, Melbourne, VIC, Australia, October 23–24, 2023, Proceedings.
Li, Y, Huang, Z, Sharma, M, Chen, L and Zhou, R, eds.
Lecture Notes in Computer Science, 14305
.
Springer, Singapore, pp. 309-320.
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| Item type | Book Section |
| URI | https://vuir.vu.edu.au/id/eprint/48102 |
| DOI | 10.1007/978-981-99-7108-4_26 |
| Official URL | https://link.springer.com/chapter/10.1007/978-981-... |
| ISBN | 9789819971077 |
| Subjects | Current > FOR (2020) Classification > 3211 Oncology and carcinogenesis Current > FOR (2020) Classification > 4603 Computer vision and multimedia computation Current > Division/Research > Institute for Sustainable Industries and Liveable Cities |
| Keywords | cancer identification; tumor; medical imaging; NSCLC |
| Download/View statistics | View download statistics for this item |
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