An application of dental X-ray image enhancement

Georgieva, Veska; Mihaylova, Antoniya D.; Petrov, Plamen

doi:10.1109/telsks.2017.8246321

Cited by 13 publications

(3 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Recently, using active contour methods is efficiently present in the colonoscopy image segmentation field. In (Georgieva et al, 2017;Sasmal et al, 2018;Dutta et al, 2018) researchers used an active contour without edges approach, i.e., Chan-Vese segmentation model to construct segmentation schemes for polyps with poor edges, i.e., not strong enough edges. The proposed methods were accompanied by various pre-processing steps and different evaluation metrics.…”

Section: Introductionmentioning

confidence: 99%

On optimization of active contour methods in colonoscopy image segmentation

Ismail

Nagy

2022

Image Anal Stereol

View full text Add to dashboard Cite

As colonoscopy is the standard screening approach for colorectal polyps, and the first step of the correct classification and the efficient automatic diagnostics is the accurate detection and segmentation of the existing polyps, it is worth researching systematically, how colonoscopy databases are responding to two of the most influential variational segmentation methods, the geodesic and Chan–Vese active contour methods. Due to the quality variation of the colonoscopy databases, pre-processing steps are made. Then, 14 various filtered images are evaluated as different inputs for the active contour methods using the Sørensen–Dice Similarity Coefficient as a performance measurement metric. The effects of the initial mask shape and its size together with the number of iterations, contraction bias and smoothness factor were studied. The number of necessary iterations depended on the image resolution. In general, the Chan-Vese method showed more efficiency to match the actual contour of the polyp than the geodesic one with an initial mask possibly located within the polyp area. Preprocessing such as reflection removal, background subtraction and mean or median filtering improve the Sørensen–Dice coefficient can improve by 0.3.

show abstract

Section: Introductionmentioning

confidence: 99%

On optimization of active contour methods in colonoscopy image segmentation

Ismail

Nagy

2022

Image Anal Stereol

View full text Add to dashboard Cite

show abstract

“…There are also techniques with hybrid approaches, which consist of the strategic combination of two or more image enhancement techniques [4,[28][29][30]. In [29], a hybrid contrast enhancement scheme based on CLAHE and morphological operations is presented. With this approach, it is possible to enhance contrast and reduce noise in dental X-ray images.…”

Section: Introductionmentioning

confidence: 99%

Panoramic Dental Radiography Image Enhancement Using Multiscale Mathematical Morphology

Román

Fretes

Adorno

et al. 2021

Sensors

View full text Add to dashboard Cite

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 Multi-Scale Top-Hat transform powered by Geodesic Reconstruction for panoramic dental radiography enhancement (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.

show abstract

“…In order to reduce noise effects in the enhanced image, a denoising function of the weighted coefficient mechanism is introduced. Georgieva et al [24] adopted an approach of CLAHE and mathematical morphological operation to detect caries in the dental image. On the other hand, the authors have applied a homomorphic denoising technique to address noisy signals and uneven distribution of the luminosity factor.…”

Section: Introductionmentioning

confidence: 99%

Evaluating spatial and frequency domain enhancement techniques on dental images to assist dental implant therapy

Shashikala¹,

Thangadurai

2021

IJECE

View full text Add to dashboard Cite

<span lang="EN-US">Dental imaging provides the patient's anatomical details for the dental implant based on the maxillofacial structure and the two-dimensional geometric projection, helping clinical experts decide whether the implant surgery is suitable for a particular patient. Dental images often suffer from problems associated with random noise and low contrast factors, which need effective preprocessing operations. However, each enhancement technique comes with some advantages and limitations. Therefore, choosing a suitable image enhancement method always a difficult task. In this paper, a universal framework is proposed that integrates the functionality of various enhancement mechanisms so that dentists can select a suitable method of their own choice to improve the quality of dental image for the implant procedure. The proposed framework evaluates the effectiveness of both frequency domain enhancement and spatial domain enhancement techniques on dental images. The selection of the best enhancement method further depends on the output image perceptibility responses, peak signal-to-noise ratio (PSNR), and sharpness. The proposed framework offers a flexible and scalable approach to the dental expert to perform enhancement of a dental image according to visual image features and different enhancement requirements.</span>

show abstract

An application of dental X-ray image enhancement

Cited by 13 publications

References 10 publications

On optimization of active contour methods in colonoscopy image segmentation

On optimization of active contour methods in colonoscopy image segmentation

Panoramic Dental Radiography Image Enhancement Using Multiscale Mathematical Morphology

Evaluating spatial and frequency domain enhancement techniques on dental images to assist dental implant therapy

Contact Info

Product

Resources

About