牙科诊断成像中的深度学习和人工智能。

IF 5.7 2区 医学 Q1 DENTISTRY, ORAL SURGERY & MEDICINE
Akitoshi Katsumata
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引用次数: 1

摘要

基于深度学习的人工智能在牙科诊断成像中的应用正在增加。一些流行的深度学习任务已经应用于牙齿诊断图像。分类任务用于对具有和不具有阳性异常发现的图像进行分类,或者基于成像发现来评估病变的进展。区域(物体)检测和分割任务已被用于全景射线照片中的牙齿识别。此技术可用于自动创建患者的牙科病历。深度学习方法也可以用于从图像中检测和评估感兴趣的解剖结构。此外,基于自然语言处理的生成人工智能可以根据诊断成像的发现自动创建书面报告。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Deep learning and artificial intelligence in dental diagnostic imaging

Deep learning and artificial intelligence in dental diagnostic imaging

Deep learning and artificial intelligence in dental diagnostic imaging

Deep learning and artificial intelligence in dental diagnostic imaging

The application of artificial intelligence (AI) based on deep learning in dental diagnostic imaging is increasing. Several popular deep learning tasks have been applied to dental diagnostic images.

Classification tasks are used to classify images with and without positive abnormal findings or to evaluate the progress of a lesion based on imaging findings. Region (object) detection and segmentation tasks have been used for tooth identification in panoramic radiographs. This technique is useful for automatically creating a patient's dental chart. Deep learning methods can also be used for detecting and evaluating anatomical structures of interest from images. Furthermore, generative AI based on natural language processing can automatically create written reports from the findings of diagnostic imaging.

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来源期刊
Japanese Dental Science Review
Japanese Dental Science Review DENTISTRY, ORAL SURGERY & MEDICINE-
CiteScore
9.90
自引率
1.50%
发文量
31
审稿时长
32 days
期刊介绍: The Japanese Dental Science Review is published by the Japanese Association for Dental Science aiming to introduce the modern aspects of the dental basic and clinical sciences in Japan, and to share and discuss the update information with foreign researchers and dentists for further development of dentistry. In principle, papers are written and submitted on the invitation of one of the Editors, although the Editors would be glad to receive suggestions. Proposals for review articles should be sent by the authors to one of the Editors by e-mail. All submitted papers are subject to the peer- refereeing process.
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