Facultad Politécnica, Universidad Nacional de Asunción, San Lorenzo 111421, Paraguay.
Facultad de Odontología, Universidad Nacional de Asunción, Asunción 001218, Paraguay.
Sensors (Basel). 2021 Apr 29;21(9):3110. doi: 10.3390/s21093110.
Panoramic dental radiography is one of the most used images of the different dental specialties. This radiography provides information about the anatomical structures of the teeth. The correct evaluation of these radiographs is associated with a good quality of the image obtained. In this study, 598 patients were consecutively selected to undergo dental panoramic radiography at the Department of Radiology of the Faculty of Dentistry, Universidad Nacional de Asunción. Contrast enhancement techniques are used to enhance the visual quality of panoramic dental radiographs. Specifically, this article presents a new algorithm for contrast, detail and edge enhancement of panoramic dental radiographs. The proposed algorithm is called (MSTHGR). This algorithm is based on multi-scale mathematical morphology techniques. The proposal extracts multiple features of brightness and darkness, through the reconstruction of the marker (obtained by the Top-Hat transformation by reconstruction) starting from the mask (obtained by the classic Top-Hat transformation). The maximum characteristics of brightness and darkness are added to the dental panoramic radiography. In this way, the contrast, details and edges of the panoramic radiographs of teeth are improved. For the tests, MSTHGR was compared with the following algorithms: Geodesic Reconstruction Multiscale Morphology Contrast Enhancement (GRMMCE), Histogram Equalization (HE), Brightness Preserving Bi-Histogram Equalization (BBHE), Dual Sub-Image Histogram Equalization (DSIHE), Minimum Mean Brightness Error Bi-Histogram Equalization (MMBEBHE), Quadri-Histogram Equalization with Limited Contrast (QHELC), Contrast-Limited Adaptive Histogram Equalization (CLAHE) and Gamma Correction (GC). Experimentally, the numerical results show that the MSTHGR obtained the best results with respect to the Contrast Improvement Ratio (CIR), Entropy (E) and Spatial Frequency (SF) metrics. This indicates that the algorithm performs better local enhancements on panoramic radiographs, improving their details and edges.
全景牙科射线照相是不同牙科专业中使用最广泛的图像之一。该射线照相提供了有关牙齿解剖结构的信息。正确评估这些射线照相与获得的图像质量有关。在这项研究中，连续选择了 598 名患者在国立亚松森大学牙科学院放射科进行牙科全景射线照相。对比度增强技术用于增强全景牙科射线照相的视觉质量。具体来说，本文提出了一种新的算法，用于增强全景牙科射线照相的对比度、细节和边缘。所提出的算法称为（MSTHGR）。该算法基于多尺度数学形态学技术。该提案通过从掩模（通过经典的 Top-Hat 变换获得）开始重建标记（通过重建获得的 Top-Hat 变换获得）来提取亮度和暗度的多个特征。最大亮度和暗度特征被添加到牙科全景射线照相中。通过这种方式，改善了牙齿全景射线照相的对比度、细节和边缘。在测试中，MSTHGR 与以下算法进行了比较：测地重建多尺度形态学对比度增强（GRMMCE）、直方图均衡化（HE）、亮度保持双直方图均衡化（BBHE）、双子图像直方图均衡化（DSIHE）、最小平均亮度误差双直方图均衡化（MMBEBHE）、四直方图均衡化与有限对比度（QHELC）、对比度限制自适应直方图均衡化（CLAHE）和伽马校正（GC）。实验结果表明，MSTHGR 在对比度改善比（CIR）、熵（E）和空间频率（SF）方面取得了最佳结果。这表明该算法在全景射线照相中执行了更好的局部增强，改善了其细节和边缘。
