RELA_Net: Upper Airway CBCT Image Segmentation Model Based on Receptive Field Expansion and Large-Kernel Attention-Reference-Cited by-同舟云学术

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RELA_Net: Upper Airway CBCT Image Segmentation Model Based on Receptive Field Expansion and Large-Kernel Attention

Published:2024 Issue: Volume:12 Page:89713-89725
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Gao Hongyong¹^ORCID,Song Weibo¹^ORCID,Cui Shulin²^ORCID,Zhou Baokang¹^ORCID,Tan Huachao¹^ORCID,Wang Qiang³

Affiliation:

1. School of Information Engineering, Dalian Ocean University, Dalian, China

2. Dalian Municipal Central Hospital, Dalian, China

3. School of Locomotive and Rolling Stock Engineering, Dalian Jiaotong University, Dalian, China

Funder

Department of Education of Liaoning Province

Capital Project of Dalian Municipal Health Commission

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10574819.pdf?arnumber=10574819

Reference45 articles.

1. Craniofacial and upper airway morphological characteristics associated with the presence and severity of obstructive sleep apnea in Chinese children

2. The influence of craniofacial morphology on the upper airway dimensions

3. Influence of Adenoid Hypertrophy on Malocclusion and Maxillofacial Development in Children

4. Ultrasonographic Evaluation of Upper Airway Structures in Children With Obstructive Sleep Apnea

5. Craniofacial and upper airway morphology in adult obstructive sleep apnea patients: A systematic review and meta-analysis of cephalometric studies

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