Denoised encoder-based residual U-net for precise teeth image segmentation and damage prediction on panoramic radiographs-Reference-Cited by-同舟云学术

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Denoised encoder-based residual U-net for precise teeth image segmentation and damage prediction on panoramic radiographs

Published:2023-10 Issue: Volume:137 Page:104651
ISSN:0300-5712
Container-title:Journal of Dentistry
language:en
Short-container-title:Journal of Dentistry

Author:

Almalki Sultan A.^ORCID,Alsubai Shtwai^ORCID,Alqahtani Abdullah^ORCID,Alenazi Adel A.

Publisher

Elsevier BV

Subject

General Dentistry

Reference23 articles.

1. TSASNet: tooth segmentation on dental panoramic X-ray images by two-stage attention segmentation network;Zhao;Knowledge- Based Syst.,2020

2. Artificial intelligence-driven novel tool for tooth detection and segmentation on panoramic radiographs;Leite;Clin. Oral Investig.,2021

3. A tooth segmentation method based on multiple geometric feature learning;Ma;Healthcare,2022

4. A symmetric fully convolutional residual network with DCRF for accurate tooth segmentation;Rao;IEEE Access,2020

5. Accuracy of advanced deep learning with tensorflow and keras for classifying teeth developmental stages in digital panoramic imaging;Mohammad;BMC Med. Imaging,2022

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1. Automated Analysis of Tooth Anatomy and Pathological Conditions from Orthopantomogram using Deep Neural Networks;IETE Journal of Research;2024-08-07

2. DeepPlaq: Dental Plaque Indexing based on Deep Neural Networks;2024-07-18

3. Intelligent Identification of Liquid Aluminum Leakage in Deep Well Casting Production Based on Image Segmentation;Applied Sciences;2024-06-24

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