A fully automatic deep learning algorithm to segment rectal Cancer on MR images: a multi-center study-Reference-Cited by-同舟云学术

A fully automatic deep learning algorithm to segment rectal Cancer on MR images: a multi-center study

Published:2022-07-11 Issue: Volume: Page:
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Container-title:2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
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Author:

Panic Jovana¹,Defeudis Arianna²,Mazzetti Simone²,Rosati Samanta¹,Giannetto Giuliana³,Micilotta Monica⁴,Vassallo Lorenzo⁵,Gatti Marco⁶,Regge Daniele²,Balestra Gabriella¹,Giannini Valentina²

Affiliation:

1. Polytechnic of Turin,Department of Electronics and Telecommunications,Turin,Italy

2. University of Turin,Department of Surgical Science,Turin,Italy

3. University of Turin,Department of Surgical Sciences - Radiology Unit,Turin,Italy

4. Candiolo Cancer Institute FPO- IRCCS,Italy

5. A. O. Ordine Mauriziano,Turin,Italy

6. Radiology Unit, SS Annunziata Savigliano Hospital,Cuneo,Italy

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9870821/9870822/09871326.pdf?arnumber=9871326

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3. Improved U-Net based on contour prediction for efficient segmentation of rectal cancer

4. MRI-based automatic segmentation of rectal cancer using 2D U-Net on two independent cohorts;knuth;Acta Oncol (Madr),2021

5. Structured Reporting of Lung Cancer Staging: A Consensus Proposal

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