Automated segmentation of kidney and renal mass and automated detection of renal mass in CT urography using 3D U-Net-based deep convolutional neural network-Reference-Cited by-同舟云学术

Automated segmentation of kidney and renal mass and automated detection of renal mass in CT urography using 3D U-Net-based deep convolutional neural network

Published:2021-01-13 Issue:7 Volume:31 Page:5021-5031
ISSN:0938-7994
Container-title:European Radiology
language:en
Short-container-title:Eur Radiol

Author:

Lin Zhiyong,Cui Yingpu,Liu Jia,Sun Zhaonan,Ma Shuai,Zhang Xiaodong,Wang Xiaoying^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s00330-020-07608-9.pdf

Reference23 articles.

1. Capitanio U, Bensalah K, Bex A et al (2019) Epidemiology of renal cell carcinoma. Eur Urol 75:74–84

2. Giménez-Bachs JM, Salinas-Sánchez AS (2019) Improving the diagnosis of renal masses: can we approach the histological diagnosis to the image? Ann Transl Med 7:56

3. Hsieh JJ, Purdue MP, Signoretti S et al (2017) Renal cell carcinoma. Nat Rev Dis Primers 3:17009

4. Bryniarski P, Kaletka Z, Życzkowski M, Prokopowicz G, Muskała B, Paradysz A (2013) Ten year treatment outcomes including blood cell count disturbances in patients with simple renal cysts. Med Sci Monit 19:518–523

5. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A (2018) Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 68:394–424

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