Improved Prognostic Prediction of Pancreatic Cancer Using Multi-phase CT by Integrating Neural Distance and Texture-Aware Transformer-Reference-Cited by-同舟云学术

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Improved Prognostic Prediction of Pancreatic Cancer Using Multi-phase CT by Integrating Neural Distance and Texture-Aware Transformer

Published:2023 Issue: Volume: Page:241-251
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Dong Hexin,Yao Jiawen,Tang Yuxing,Yuan Mingze,Xia Yingda,Zhou Jian,Lu Hong,Zhou Jingren,Dong Bin,Lu Le,Liu Zaiyi,Zhang Li,Shi Yu,Zhang Ling

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-43904-9_24

Reference25 articles.

1. Attiyeh, M.A., et al.: Survival prediction in pancreatic ductal adenocarcinoma by quantitative computed tomography image analysis. Ann. Surg. Oncol. 25(4), 1034–1042 (2018)

2. Bian, Y., et al.: Artificial intelligence to predict lymph node metastasis at CT in pancreatic ductal adenocarcinoma. Radiology 306(1), 160–169 (2023)

3. Cheng, N.M., et al.: Deep learning for fully automated prediction of overall survival in patients with oropharyngeal cancer using FDG-PET imaging. Clin. Cancer Res. 27(14), 3948–3959 (2021)

4. Dosovitskiy, A., et al.: An image is worth 16x16 words: transformers for image recognition at scale. In: ICLR (2021)

5. Ducreux, M., et al.: Cancer of the pancreas: ESMO clinical practice guidelines for diagnosis, treatment and follow-up. Ann. Oncol. 26, v56–v68 (2015)

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