ArticleOral radiology2023
Evaluation of histogram equalization and contrast limited adaptive histogram equalization effect on image quality and fractal dimensions of digital periapical radiographs.
Article in Oral radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed.
- Histogram-Corrected Intraoral Photographs for Early Gingivitis Screening in Orthodontic Patients.International journal of dental hygiene · 2026Article
- Machine learning in cancer imaging for enhanced precision in diagnosis and therapy.Discover computing · 2026Review
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- Improving Endodontic Radiograph Interpretation with TV-CLAHE for Enhanced Root Canal Detection.Journal of clinical medicine · 2025Article
- Application of image enhancement in the auxiliary diagnosis of oral potentially malignant disorders.Clinical oral investigations · 2025Article
- Deep learning in gonarthrosis classification: a comparative study of model architectures and single vs. multi-model methods.Frontiers in artificial intelligence · 2025Article
- Multi-label dental disorder diagnosis based on MobileNetV2 and swin transformer using bagging ensemble classifier.Scientific reports · 2024Article
- Detection of Cervical Foraminal Stenosis from Oblique Radiograph Using Convolutional Neural Network Algorithm.Yonsei medical journal · 2024Article
- Evaluation of the effects of postprocessing settings in digital bitewing radiographs on proximal caries detection.Clinical and experimental dental research · 2024Article
- Evaluating the effect of amalgam fillings on caries detection in cone-beam computed tomography images.Dental research journal · 2024Article
- Construction of multi-scale feature fusion segmentation model of MRI knee images based on dual attention mechanism weighted aggregation.Technology and health care : official journal of the European Society for Engineering and Medicine · 2024Article
- Multi-Scale FPGA-Based Infrared Image Enhancement by Using RGF and CLAHE.Sensors (Basel, Switzerland) · 2023Article
- Evaluation of deep learning and convolutional neural network algorithms accuracy for detecting and predicting anatomical landmarks on 2D lateral cephalometric images: A systematic review andThe Saudi dental journal · 2023Review
- Accuracy of tooth-implant impressions: Comparison of five different techniques.Clinical and experimental dental research · 2023Review
- Evaluation of the effect of amalgam fillings on the diagnosis of proximal caries using cone-beam computed tomography technique.Dental research journal · 2023Article
- The Effect of Ferrule/Crown Ratio and Post Length on the Applied Stress and Strain Distribution to the Endodontically Treated Maxillary Central Teeth: A Finite Element Analysis.Frontiers in dentistry · 2023Article
- Does a New Modification of the Two-Step Injection Technique for Inferior Alveolar Nerve Block Reduce Pain Compared to the Conventional Technique? A Randomized Clinical Trial.International journal of dentistry · 2023Article
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3 authors.
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Abstract
objectivesThis study aims to evaluate the effects of histogram equalization (HE) and contrast limited adaptive histogram equalization (CLAHE) on periapical images and fractal dimensions in the periapical region.
methodsIn this cross-sectional study, digital periapical images were selected from the archive of Dentistry School of Isfahan University of Medical Sciences. The radiographs were taken from mandibular and maxillary anterior single root teeth with healthy root and periodontium. After applying HE and CLAHE algorithms to images, two radiologists evaluated the quality of apex detection from using a 5-point Likert scale (from 5 for very good image quality to 1 for very bad image quality). Afterward, all the images were imported to the ImageJ application, and the region of interest (ROI) was specified as the region between the two central incisors. The fractal box-counting method was used to determine fractal dimensions (FD) values. Nonparametric Wilcoxon-Friedman test, Intraclass Correlation Coefficient test, T-test, and Pair T-test were performed as statistical analysis (α = 0.05).
resultsFifty-three radiographs were analyzed and the image quality assessments were significantly different between raw images and images after performing HE, CLAHE (p value < 0.001), and using CLAHE algorithm significantly increases image quality assessments more than HE (p value = 0.009). There was a significant difference in FD values for images after applying CLAHE and HE compared to raw images (p value < 0.001), and HE decreased the FD value significantly more than CLAHE (p value = 0.019).
conclusionsEmploying CLAHE and HE algorithm via OpenCV python library improves the periapical image quality, which is more significant using the CLAHE algorithm. Moreover, applying CLAHE and HE reduces trabecular bone structure detection and FD values in periapical images, especially in HE.
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