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Automatic kidney segmentation using 2.5D ResUNet and 2.5D DenseUNet for malignant potential analysis in complex renal cyst based on CT images

Published Online: 2022-03-22

Published Print: 2022-12

Authors

Kittipongdaja, Parin

Siriborvornratanakul, Thitirat https://orcid.org/0000-0002-6530-5302
License Information

Text and Data Mining valid from 2022-03-22

Version of Record valid from 2022-03-22
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Article History

Received: 7 May 2021

Accepted: 23 February 2022

First Online: 22 March 2022

Declarations

:

: To retrieve abdominal CT images from the hospital’s database, we follow the principles of Helsinki Declaration and under Medical Research Involving Human Subjects Act. The protocol of this research is approved by the ethics committee of Ramathibodi hospital. In addition, the need for individual informed consent is waived by the ethics committee of Ramathibodi hospital, Bangkok, Thailand.

: The authors declare that they have no competing interests.

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