Development and multicenter validation of deep convolutional neural network–based detection of colorectal cancer on abdominal CT
Author:
Funder
Ministry of Education
Korea University Anam Hospital
Ministry of Health and Welfare
Publisher
Springer Science and Business Media LLC
Subject
Radiology, Nuclear Medicine and imaging,General Medicine
Link
https://link.springer.com/content/pdf/10.1007/s00330-023-10452-2.pdf
Reference8 articles.
1. Pacal I, Karaboga D, Basturk A, Akay B, Nalbantoglu U (2020) A comprehensive review of deep learning in colon cancer. Comput Biol Med. https://doi.org/10.1016/j.compbiomed.2020.104003
2. Lee SA, Poh A (2015) Unsuspected colorectal carcinoma on routine abdominopelvic computed tomography. Singapore Med J. https://doi.org/10.11622/smedj.2015072
3. Spada C, Hassan C, Bellini D et al (2021) Imaging alternatives to colonoscopy: CT colonography and colon capsule. European Society of Gastrointestinal Endoscopy (ESGE) and European Society of Gastrointestinal and Abdominal Radiology (ESGAR) Guideline - Update 2020. Eur Radiol. https://doi.org/10.1007/s00330-020-07413-4
4. Pickhardt PJ (2022) Value-added opportunistic ct screening: state of the art. Radiology. https://doi.org/10.1148/radiol.211561
5. Isensee F, Petersen J, Kohl SAA, Jäger PF, Maier-Hein KH (2019) nnU-Net: breaking the spell on successful medical image segmentation. arXiv. https://doi.org/10.48550/arXiv.1904.08128
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