Toothsegnet: Image Degradation Meets Tooth Segmentation in CBCT Images-Reference-Cited by-同舟云学术

Toothsegnet: Image Degradation Meets Tooth Segmentation in CBCT Images

Published:2023-04-18 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI)
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Author:

Liu Jiaxiang¹,Hu Tianxiang¹,Feng Yang²,Ding Wanghui³,Liu Zuozhu¹

Affiliation:

1. Zhejiang University-University of Illinois at Urbana-Champaign Institute, Zhejiang University

2. Angelalign Inc

3. Zhejiang University School of Medicine,Stomatology Hospital, School of Stomatology

Funder

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10230311/10230322/10230557.pdf?arnumber=10230557

Reference19 articles.

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2. Image Quality Assessment: From Error Visibility to Structural Similarity

3. Fully convolutional networks for semantic segmentation

4. Unet++: A nested u-net architecture for medical image segmentation;zhou;Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support,2018

5. Uctransnet: Rethinking the skip connections in u-net from a channel-wise perspective with transformer;wang,2021

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