Improved soft-tissue visibility on cone-beam computed tomography with an image-generating artificial intelligence model using a cyclic generative adversarial network.

IF 1.6 3区 医学 Q3 DENTISTRY, ORAL SURGERY & MEDICINE
Oral Radiology Pub Date : 2024-10-01 Epub Date: 2024-06-28 DOI:10.1007/s11282-024-00763-5
Motoki Fukuda, Michihito Nozawa, Hironori Akiyama, Eiichiro Ariji, Yoshiko Ariji
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引用次数: 0

Abstract

Objectives: The objective of this study was to enhance the visibility of soft tissues on cone-beam computed tomography (CBCT) using a CycleGAN network trained on CT images.

Methods: Training and evaluation of the CycleGAN were conducted using CT and CBCT images collected from Aichi Gakuin University (α facility) and Osaka Dental University (β facility). Synthesized images (sCBCT) output by the CycleGAN network were evaluated by comparing them with the original images (oCBCT) and CT images, and assessments were made using histogram analysis and human scoring of soft-tissue anatomical structures and cystic lesions.

Results: The histogram analysis showed that on sCBCT, soft-tissue anatomical structures showed significant shifts in voxel intensity toward values resembling those on CT, with the mean values for all structures approaching those of CT and the specialists' visibility scores being significantly increased. However, improvement in the visibility of cystic lesions was limited.

Conclusions: Image synthesis using CycleGAN significantly improved the visibility of soft tissue on CBCT, with this improvement being particularly notable from the submandibular region to the floor of the mouth. Although the effect on the visibility of cystic lesions was limited, there is potential for further improvement through refinement of the training method.

Abstract Image

利用循环生成对抗网络的图像生成人工智能模型提高锥束计算机断层扫描的软组织可见度。
研究目的本研究的目的是利用在 CT 图像上训练的 CycleGAN 网络提高锥束计算机断层扫描(CBCT)上软组织的可见度:方法:使用从爱知学院大学(α 设备)和大阪牙科大学(β 设备)收集的 CT 和 CBCT 图像对 CycleGAN 进行了训练和评估。通过与原始图像(oCBCT)和 CT 图像比较,对 CycleGAN 网络输出的合成图像(sCBCT)进行了评估,并使用直方图分析和对软组织解剖结构和囊性病变的人体评分进行了评估:直方图分析表明,在 sCBCT 上,软组织解剖结构的体素强度明显向 CT 上的值靠拢,所有结构的平均值都接近 CT 值,专家的可见度评分也明显提高。然而,囊性病变的可见度提高有限:结论:使用 CycleGAN 进行图像合成可显著提高 CBCT 对软组织的可见度,尤其是从颌下腺区到口底的可见度提高尤为明显。虽然对囊性病变可见度的影响有限,但通过改进训练方法,仍有可能进一步提高可见度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Oral Radiology
Oral Radiology DENTISTRY, ORAL SURGERY & MEDICINE-
CiteScore
4.20
自引率
13.60%
发文量
87
审稿时长
>12 weeks
期刊介绍: As the official English-language journal of the Japanese Society for Oral and Maxillofacial Radiology and the Asian Academy of Oral and Maxillofacial Radiology, Oral Radiology is intended to be a forum for international collaboration in head and neck diagnostic imaging and all related fields. Oral Radiology features cutting-edge research papers, review articles, case reports, and technical notes from both the clinical and experimental fields. As membership in the Society is not a prerequisite, contributions are welcome from researchers and clinicians worldwide.
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