Automatic orbital segmentation using deep learning-based 2D U-net and accuracy evaluation: A retrospective study-Reference-Cited by-同舟云学术

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Automatic orbital segmentation using deep learning-based 2D U-net and accuracy evaluation: A retrospective study

Published:2023-10 Issue:10 Volume:51 Page:609-613
ISSN:1010-5182
Container-title:Journal of Cranio-Maxillofacial Surgery
language:en
Short-container-title:Journal of Cranio-Maxillofacial Surgery

Author:

Morita Daiki^ORCID,Kawarazaki Ayako,Koimizu Jungen^ORCID,Tsujiko Shoko^ORCID,Soufi Mazen,Otake Yoshito,Sato Yoshinobu,Numajiri Toshiaki

Publisher

Elsevier BV

Subject

Otorhinolaryngology,Oral Surgery,Surgery

Reference44 articles.

1. Medical image analysis using convolutional neural networks: a review;Anwar;J. Med. Syst.,2018

2. Treatment of orbital floor fracture using a periosteum-polymer complex;Asamura;J. Cranio-Maxillo-Fac. Surg.,2010

3. Retrospective analysis of 301 patients with orbital floor fracture;Bartoli;J. Cranio-Maxillo-Fac. Surg.,2015

4. In-house 3D model printing for acute cranio-maxillo-facial trauma surgery: process, time, and costs;Bergeron;Plast Reconstr Surg Glob Open,2021

5. Surgical outcomes of orbital fracture reconstruction using patient-specific implants;Blumer;J. Oral Maxillofac. Surg.,2021

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