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利用TV-CLAHE改进牙髓X线片解读以增强根管检测

Improving Endodontic Radiograph Interpretation with TV-CLAHE for Enhanced Root Canal Detection.

作者信息

Obuchowicz Barbara, Zarzecka Joanna, Strzelecki Michał, Jakubowska Marzena, Obuchowicz Rafał, Piórkowski Adam, Zarzecka-Francica Elżbieta, Lasek Julia

机构信息

Department of Conservative Dentistry with Endodontics, Jagiellonian University Collegium Medicum, Montelupich 4, 31-155 Cracow, Poland.

Institute of Electronics, Lodz University of Technology, 93-590 Lodz, Poland.

出版信息

J Clin Med. 2025 Aug 6;14(15):5554. doi: 10.3390/jcm14155554.

Abstract

The accurate visualization of root canal systems on periapical radiographs is critical for successful endodontic treatment. This study aimed to evaluate and compare the effectiveness of several image enhancement algorithms-including a novel Total Variation-Contrast-Limited Adaptive Histogram Equalization (TV-CLAHE) technique-in improving the detectability of root canal configurations in mandibular incisors, using cone-beam computed tomography (CBCT) as the gold standard. A null hypothesis was tested, assuming that enhancement methods would not significantly improve root canal detection compared to original radiographs. A retrospective analysis was conducted on 60 periapical radiographs of mandibular incisors, resulting in 420 images after applying seven enhancement techniques: Histogram Equalization (HE), Contrast-Limited Adaptive Histogram Equalization (CLAHE), CLAHE optimized with Pelican Optimization Algorithm (CLAHE-POA), Global CLAHE (G-CLAHE), k-Caputo Fractional Differential Operator (KCFDO), and the proposed TV-CLAHE. Four experienced observers (two radiologists and two dentists) independently assessed root canal visibility. Subjective evaluation was performed using an own scale inspired by a 5-point Likert scale, and the detection accuracy was compared to the CBCT findings. Quantitative metrics including Peak Signal-to-Noise Ratio (PSNR), Signal-to-Noise Ratio (SNR), image entropy, and Structural Similarity Index Measure (SSIM) were calculated to objectively assess image quality. Root canal detection accuracy improved across all enhancement methods, with the proposed TV-CLAHE algorithm achieving the highest performance (93-98% accuracy), closely approaching CBCT-level visualization. G-CLAHE also showed substantial improvement (up to 92%). Statistical analysis confirmed significant inter-method differences ( < 0.001). TV-CLAHE outperformed all other techniques in subjective quality ratings and yielded superior SNR and entropy values. Advanced image enhancement methods, particularly TV-CLAHE, significantly improve root canal visibility in 2D radiographs and offer a practical, low-cost alternative to CBCT in routine dental diagnostics. These findings support the integration of optimized contrast enhancement techniques into endodontic imaging workflows to reduce the risk of missed canals and improve treatment outcomes.

摘要

根尖片上根管系统的准确可视化对于成功的根管治疗至关重要。本研究旨在评估和比较几种图像增强算法——包括一种新颖的全变差-对比度受限自适应直方图均衡化(TV-CLAHE)技术——在提高下颌切牙根管形态可检测性方面的有效性,以锥形束计算机断层扫描(CBCT)作为金标准。检验了一个零假设,即假设与原始根尖片相比,增强方法不会显著提高根管检测效果。对60张下颌切牙的根尖片进行回顾性分析,在应用七种增强技术后得到420张图像:直方图均衡化(HE)、对比度受限自适应直方图均衡化(CLAHE)、用鹈鹕优化算法优化的CLAHE(CLAHE-POA)、全局CLAHE(G-CLAHE)、k-卡普托分数阶微分算子(KCFDO)以及所提出的TV-CLAHE。四名经验丰富的观察者(两名放射科医生和两名牙医)独立评估根管的可见性。使用受5点李克特量表启发的自有量表进行主观评估,并将检测准确性与CBCT结果进行比较。计算包括峰值信噪比(PSNR)、信噪比(SNR)、图像熵和结构相似性指数测量(SSIM)在内的定量指标,以客观评估图像质量。所有增强方法的根管检测准确性均有所提高,所提出的TV-CLAHE算法表现最佳(准确率为93 - 98%),接近CBCT级别的可视化效果。G-CLAHE也有显著改善(高达92%)。统计分析证实方法间存在显著差异(<0.001)。TV-CLAHE在主观质量评分方面优于所有其他技术,并产生了更高的SNR和熵值。先进的图像增强方法,特别是TV-CLAHE,显著提高了二维根尖片中根管的可见性,并在常规牙科诊断中提供了一种实用、低成本的替代CBCT的方法。这些发现支持将优化的对比度增强技术整合到根管成像工作流程中,以降低遗漏根管的风险并改善治疗效果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb49/12347500/cbbeed372304/jcm-14-05554-g001.jpg

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