Study of edge detection task in dental panoramic radiographs

Gráfová, Lucie; Kašparová, Martina; Kakawand, S; Procházka, Aleš

doi:10.1259/dmfr.20120391

Cited by 22 publications

(19 citation statements)

References 25 publications

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“…Digitalization of plaster casts are performed either by the 3D scanning or by processing of their stereophotos allowing to use numerical methods for evaluation of specific measures of dental arch [23,24]. To detect individual image components it was necessary to apply image de-noising and segmentation methods including watershed transform, region growing and Hough transform to evaluate distances between individual teeth before and after the treatment according to Figs 6(a) and (b).…”

Section: Segmentation and Three-dimensional Modelling In Orthodontiamentioning

confidence: 99%

History and biomedical applications of digital signal and image processing

Procházka

Vyšata

2014

2014 International Workshop on Computational Intelligence for Multimedia Understanding (IWCIM)

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The paper presents in its initial part historical notes to the development of digital signal and image processing methods. The following case studies are devoted to their application in biomedicine and they include the use of computational intelligence in EEG and EMG signal processing, image segmentation and registration in orthodontia, the human-machine interaction and the three-dimensional modelling using MS Kinect in diagnostics and treatment of human motion disorders and neurological diseases. Associated comments include remarks and references to the development of modern computational tools, biosensors, wireless communication and data fusion used in assistive technologies and robotic systems. Mathematical tools common to all these applications form the next part of the paper that includes notes to spectral analysis, functional transforms, digital filtering, image enhancement, classification of multi-dimensional signal components and optimization using neural networks. Final remarks emphasize the interdisciplinary significance of the digital signal processing forming the integrating basis of many diverse research areas.Index Termshistory of digital signal and image processing, computational intelligence, digital signal processing methods, computer aided biomedical diagnostics and treatment, Microsoft Kinect three-dimensional modelling

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Section: Segmentation and Three-dimensional Modelling In Orthodontiamentioning

confidence: 99%

History and biomedical applications of digital signal and image processing

Procházka

Vyšata

2014

2014 International Workshop on Computational Intelligence for Multimedia Understanding (IWCIM)

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“…For instance in orthopantograms, the Canny algorithm was found to be superior to other tested common methods for qualitative landmark detection [4]. In chest radiographs the Sobel operator was found to be superior to the Roberts operator in detecting edges; however, the Canny algorithm, amongst other common methods, was not studied [34].…”

Section: Introductionmentioning

confidence: 99%

“…Edge detection is considered an important and primary step in many analyses and for that reason, it is under continuous research. [3] Its operators and algorithms have been extensively employed in the digital analysis of images from various kinds of medical imaging techniques such as: radiography [4][5][6][7][8], mammography [9], ultrasonography [10,11], echocardiography [12], computed tomography [13], magnetic resonance [14][15][16][17], radioisotope scanning [18], positron emission tomography [19], optical coherence tomography [20,21], near-infrared [22], fundography [23][24][25][26][27], angiography [28], microscopy [29], confocal microscopy [30][31][32] and prosthetic vision [33].…”

Section: Introductionmentioning

confidence: 99%

“…Nevertheless, the literature lacks a large scale study that specifically tests edge detection techniques, both quantitatively and qualitatively, for use in analyzing medical images. Additionally, the vast majority of studies carried out on edge detection employed high-level mathematical packages, such as the MATLAB environment [4,5,7,10,15,19,[25][26][27]30], to perform their analyses; however, although these programs are powerful, they are not readily available for wide use and are not always needed for simpler functions.…”

Section: Introductionmentioning

confidence: 99%

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Comparison of Edge Detection Algorithms for Automated Radiographic Measurement of the Carrying Angle

AlNouri

Saei

Younis

et al. 2015

JBEMi

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Many geometrical angles are measured directly on bone radiographs and are difficult to recall, we wanted to explore an automatic method of measurement. Edge detection was needed to determine bone edges and use them for calculation. There is no consensus on which is the best one for use in skeletal radiographs. We decided to compare commonly used edge detection methods qualitatively and quantitatively for measuring the carrying angle of the elbow using a framework we developed in PHP: Hypertext Preprocessor. Five-Hundred patients' elbow radiographs were collected. They were run through the measurement algorithm using the following edge detection methods: Sobel, Scharr, Prewitt, Frei-Chen, Kirsch, Robinson, Difference of Gaussians (DoG), Laplacian of Gaussian (LoG), Canny, Hough. Five observers manually measured the carrying angle. Results were compared using Intraclass Correlation Coefficient (ICC), Regression Analysis and Validity calculation. The Robinson algorithm was best in the qualitative analysis. Observer ICC was 0.643 which showed a strong agreement. Quantitative analysis revealed that, developing bone caused a significant bias compared to mature bone and DoG algorithm was the best due to low bias, high validity and low processing time. Automated radiographic measurement of the carrying angle of the elbow is a feasible and reliable process.

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“…It forms a contribution to the study of dental arch parameters using segmentation, classification and registration [37,38] of orthodontic data.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of dental morphometrics during the orthodontic treatment

et al. 2014

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BackgroundDiagnostic orthodontic and prosthetic procedures commence with an initial examination, during which a number of individual findings on occlusion or malocclusion are clarified. Nowadays we try to replace standard plaster casts by scanned objects and digital models.MethodGeometrically calibrated images aid in the comparison of several different steps of the treatment and show the variation of selected features belonging to individual biomedical objects. The methods used are based on geometric morphometrics, making a new approach to the evaluation of the variability of features. The study presents two different methods of measurement and shows their accuracy and reliability.ResultsThe experimental part of the present paper is devoted to the analysis of the dental arch objects of 24 patients before and after the treatment using the distances between the canines and premolars as the features important for diagnostic purposes. Our work proved the advantage of measuring digitalized orthodontic models over manual measuring of plaster casts, with statistically significant results and accuracy sufficient for dental practice.ConclusionA new method of computer imaging and measurements of a dental stone cast provides information with the precision required for orthodontic treatment. The results obtained point to the reduction in the variance of the distances between the premolars and canines during the treatment, with a regression coefficient RC=0.7 and confidence intervals close enough for dental practice. The ratio of these distances pointed to the nearly constant value of this measure close to 0.84 for the given set of 24 individuals.

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Study of edge detection task in dental panoramic radiographs

Cited by 22 publications

References 25 publications

History and biomedical applications of digital signal and image processing

History and biomedical applications of digital signal and image processing

Comparison of Edge Detection Algorithms for Automated Radiographic Measurement of the Carrying Angle

Evaluation of dental morphometrics during the orthodontic treatment

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