2022
DOI: 10.1049/ipr2.12416
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The local ternary pattern encoder–decoder neural network for dental image segmentation

Abstract: Recent advances in medical imaging analyses, especially the use of deep learning, are helping to identify, detect, classify, and quantify patterns in radiographs. At the centre of these advances is the ability to explore hierarchical feature representations learned from data. Deep learning is invaluably becoming the most sought out technique, leading to enhanced performances in the analysis of medical applications and systems. Deep learning techniques have achieved improved performance results in dental image … Show more

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Cited by 4 publications
(1 citation statement)
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“…For improving dental disease diagnosis and treatment plans, deep learning [7] has significantly influenced the processing of intraoral X-ray images in image processing [8], segmentation [9][10][11][12] and enhancements [13][14][15]. These developments integrating intraoral X-ray imaging with deep learning techniques enhance the precision of oral health condition recognition and detection, such as dental caries [16][17][18][19][20][21][22], implant [23], oriented tooth [24], restoration by filling [25] and dental material [26].…”
Section: Introductionmentioning
confidence: 99%
“…For improving dental disease diagnosis and treatment plans, deep learning [7] has significantly influenced the processing of intraoral X-ray images in image processing [8], segmentation [9][10][11][12] and enhancements [13][14][15]. These developments integrating intraoral X-ray imaging with deep learning techniques enhance the precision of oral health condition recognition and detection, such as dental caries [16][17][18][19][20][21][22], implant [23], oriented tooth [24], restoration by filling [25] and dental material [26].…”
Section: Introductionmentioning
confidence: 99%