Comparison of Preprocessing Techniques for Dental Image Analysis

2020 ◽  
Vol 16 (7) ◽  
pp. 776-780
Author(s):  
Arockia Sukanya ◽  
Kamalanand Krishnamurthy ◽  
Thayumanavan Balakrishnan
Keyword(s):  
Performance Measures ◽  
Signal To Noise Ratio ◽  
Histogram Equalization ◽  
X Rays ◽  
Human Teeth ◽  
Radiographic Images ◽  
Pass Filter ◽  
Hybrid Metaheuristic ◽  
Dental Radiographs ◽  
Classification Of Images

Various dental disorders, such as lesions, masses, carries, etc. may affect the human dental structure. Dental radiography is a technique, which passes X-rays through dental structures and records the radiographic images. These radiographic images are used to analyze the disorders present in the human teeth. Preprocessing is a primary step to enhance the radiographic images for further segmentation and classification of images. In this work, the preprocessing techniques such as unsharp masking using high pass filter, bi-level histogram equalization and hybrid metaheuristic have been utilized for dental radiographs. The performance measures of the preprocessing techniques were analyzed. Results demonstrate that a hybrid metaheuristic algorithm for dental radiographs achieves higher performance measures when compared to other enhancement methods. An average Peak Signal-to-Noise Ratio (PSNR) value of 21.6 was observed in the case of a hybrid metaheuristic technique for dental image enhancement.

Comparison of the performance of three domain transform filters for radiographic contrast enhancement of welded objects

2020 ◽  
Vol 62 (6) ◽  
pp. 352-356
Author(s):  
E Yahaghi ◽  
M E Hosseini-Ashrafi
Keyword(s):  
Contrast Enhancement ◽  
Signal To Noise Ratio ◽  
Image Features ◽  
Image Contrast ◽  
X Rays ◽  
Radiographic Images ◽  
Recursive Filtering ◽  
Image Contrast Enhancement ◽  
Image Detail

Weld quality inspection using industrial radiography is considered to be one of the most important processes in critical industries such as aeronautical manufacturing. The quality of radiographic images of welded industrial parts may suffer from poor signal-to-noise ratio (SNR), the main cause of which is the unavoidable detection of scattered X-rays. Image processing methods may be used to enhance image contrast and achieve improved defect detection. In this study, the outcomes from three different image contrast enhancement spatial domain transform algorithms are analysed and compared. The three algorithms used are normalised convolution (NC), interpolated convolution (IC) and recursive filtering (RF). Based on the results of qualitative operator perception, the study shows that the application of all three methods results in improved image contrast, enabling enhanced visualisation of image detail. Subtle differences in performance between the outputs from the different algorithms are noted, especially around the edges of image features. Furthermore, it is found that RF is approximately two orders of magnitude quicker than the other algorithms, making it more suitable for online weld inspection lines.

scholarly journals Principles and Perspectives of Radiographic Imaging with Muons

2021 ◽  
Vol 7 (12) ◽  
pp. 253
Author(s):  
Luigi Cimmino
Keyword(s):  
Signal To Noise Ratio ◽  
Wide Spectrum ◽  
Muon Flux ◽  
X Rays ◽  
Radiographic Imaging ◽  
Time Data ◽  
Radiographic Images ◽  
High Background ◽  
Background Rejection ◽  
Long Time

Radiographic imaging with muons, also called Muography, is based on the measurement of the absorption of muons, generated by the interaction of cosmic rays with the earth’s atmosphere, in matter. Muons are elementary particles with high penetrating power, a characteristic that makes them capable of crossing bodies of dimensions of the order of hundreds of meters. The interior of bodies the size of a pyramid or a volcano can be seen directly with the use of this technique, which can rely on highly segmented muon trackers. Since the muon flux is distributed in energy over a wide spectrum that depends on the direction of incidence, the main difference with radiography made with X-rays is in the source. The source of muons is not tunable, neither in energy nor in direction; to improve the signal-to-noise ratio, muography requires large instrumentation, long time data acquisition and high background rejection capacity. Here, we present the principles of the Muography, illustrating how radiographic images can be obtained, starting from the measurement of the attenuation of the muon flux through an object. It will then be discussed how recent technologies regarding artificial intelligence can give an impulse to this methodology in order to improve its results.

scholarly journals Comparison of Image Improvement Method on Parasite Images of Malaria

2018 ◽  
Vol 2 (2) ◽  
pp. 101-110
Author(s):  
Rika Rosnelly ◽  
Linda Wahyuni
Keyword(s):  
Image Quality ◽  
Malaria Parasite ◽  
Signal To Noise Ratio ◽  
Histogram Equalization ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Gaussian Filtering ◽  
Low Pass ◽  
Image Improvement ◽  
Contrast Stretching

Improved image is a process on the image that initially has a quality that is less good or has noise. In this image improvement operation image quality will be improved so that the image produces better quality. Image improvement methods used are contrast stretching, histogram equalization, low pass filter and Gaussian filtering. In this study compare contrast stretching method, histogram equalization, low pass filter and Gaussian filtering to improve image quality. Performance of each method would be calculated by finding the value of Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR). This study compares contrast stretching methods, histogram equalization, low pass filter and Gaussian filtering to improve image quality. Total data of malaria parasite image is 120. The data consist of image of malaria parasite falciparum, vivax, malariae along with stage that is ring, tropozoit, skizon and gametocyte. Evaluate the performance of each method by finding Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) values. The result is a contrast stretching provides better image quality against malaria parasite image.

Image Quality Enhancing by Efficient Histogram Equalization

2014 ◽  
Vol 2 (2) ◽  
pp. 47-58
Author(s):  
Ismail Sh. Baqer
Keyword(s):  
Image Quality ◽  
Contrast Enhancement ◽  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Histogram Equalization ◽  
Gray Level ◽  
Signal To Noise ◽  
Squared Error ◽  
Noise Ratio

A two Level Image Quality enhancement is proposed in this paper. In the first level, Dualistic Sub-Image Histogram Equalization DSIHE method decomposes the original image into two sub-images based on median of original images. The second level deals with spikes shaped noise that may appear in the image after processing. We presents three methods of image enhancement GHE, LHE and proposed DSIHE that improve the visual quality of images. A comparative calculations is being carried out on above mentioned techniques to examine objective and subjective image quality parameters e.g. Peak Signal-to-Noise Ratio PSNR values, entropy H and mean squared error MSE to measure the quality of gray scale enhanced images. For handling gray-level images, convenient Histogram Equalization methods e.g. GHE and LHE tend to change the mean brightness of an image to middle level of the gray-level range limiting their appropriateness for contrast enhancement in consumer electronics such as TV monitors. The DSIHE methods seem to overcome this disadvantage as they tend to preserve both, the brightness and contrast enhancement. Experimental results show that the proposed technique gives better results in terms of Discrete Entropy, Signal to Noise ratio and Mean Squared Error values than the Global and Local histogram-based equalization methods

scholarly journals 405 Radiological Analysis of Gentamicin Eluting Synthetic Bone Graft Substitute Used in The Management of Gustilo IIIB Open Fractures

2021 ◽  
Vol 108 (Supplement_2) ◽  
Author(s):  
A Aljawadi ◽  
I Madhi ◽  
T Naylor ◽  
M Elmajee ◽  
A Islam ◽  
...  
Keyword(s):  
Bone Graft ◽  
Cortical Thickness ◽  
Bone Graft Substitute ◽  
Fracture Site ◽  
Open Fractures ◽  
X Rays ◽  
Radiographic Images ◽  
Synthetic Bone ◽  
Synthetic Bone Graft

Abstract Background Management of traumatic bone void associated with Gustilo IIIB open fractures is challenging. Gentamicin eluting synthetic bone graft substitute (Cerament-G) had been recently utilised for the management of patients with these injuries. This study aims to assess radiological signs of Cerament-G remodelling. Method Retrospective data analysis of all patients admitted to our unit with IIIB open fractures who had Cerament-G applied as avoid filler. Postoperative radiographic images of the fracture site at 6-weeks, 3-months, 6-months and at the last follow-up were reviewed. The radiological signs of Cerament-G integration, percent of void healing, and bone cortical thickness at the final follow-up were assessed. Results 34 patients met our inclusion criteria, mean age: 42 years. Mean follow-up time was 20 months. 59% of patients had excellent (>90%) void filling, 26.4% of patients had 50-90% void filling, and 14.6% had < 50% void filling. Normal bone cortical thickness was restored on AP and Lateral views in 55.8% of patients. No residual Cerement-G was seen on X-rays at the final follow-up in any of the patients. Conclusions Our results showed successful integration of Cerament-G with excellent void filling and normal cortical thickness achieved in more than half of the patients.

Visualizing Fluid Flows With X-Rays

2007 ◽  
Author(s):  
Theodore J. Heindel ◽  
Terrence C. Jensen ◽  
Joseph N. Gray
Keyword(s):  
Computed Tomography ◽  
Flow Visualization ◽  
Three Dimensional ◽  
Fluid Flows ◽  
X Rays ◽  
Radiographic Images ◽  
Optical Access ◽  
X Ray ◽  
X Ray Computed ◽  
Density Map

There are several methods available to visualize fluid flows when one has optical access. However, when optical access is limited to near the boundaries or not available at all, alternative visualization methods are required. This paper will describe flow visualization using an X-ray system that is capable of digital X-ray radiography, digital X-ray stereography, and digital X-ray computed tomography (CT). The unique X-ray flow visualization facility will be briefly described, and then flow visualization of various systems will be shown. Radiographs provide a two-dimensional density map of a three dimensional process or object. Radiographic images of various multiphase flows will be presented. When two X-ray sources and detectors simultaneously acquire images of the same process or object from different orientations, stereographic imaging can be completed; this type of imaging will be demonstrated by trickling water through packed columns and by absorbing water in a porous medium. Finally, local time-averaged phase distributions can be determined from X-ray computed tomography (CT) imaging, and this will be shown by comparing CT images from two different gas-liquid sparged columns.

scholarly journals Non-Linear Hopped Chaos Parameters-Based Image Encryption Algorithm Using Histogram Equalization

Entropy ◽  
2021 ◽  
Vol 23 (5) ◽  
pp. 535
Author(s):  
Karim H. Moussa ◽  
Ahmed I. El Naggary ◽  
Heba G. Mohamed
Keyword(s):  
Image Encryption ◽  
Initial Conditions ◽  
Signal To Noise Ratio ◽  
Chaotic Map ◽  
Histogram Equalization ◽  
Encryption Algorithm ◽  
Multimedia Contents ◽  
Encryption Schemes ◽  
Change Intensity ◽  
Increasing Demand

Multimedia wireless communications have rapidly developed over the years. Accordingly, an increasing demand for more secured media transmission is required to protect multimedia contents. Image encryption schemes have been proposed over the years, but the most secure and reliable schemes are those based on chaotic maps, due to the intrinsic features in such kinds of multimedia contents regarding the pixels’ high correlation and data handling capabilities. The novel proposed encryption algorithm introduced in this article is based on a 3D hopping chaotic map instead of fixed chaotic logistic maps. The non-linearity behavior of the proposed algorithm, in terms of both position permutation and value transformation, results in a more secured encryption algorithm due to its non-convergence, non-periodicity, and sensitivity to the applied initial conditions. Several statistical and analytical tests such as entropy, correlation, key sensitivity, key space, peak signal-to-noise ratio, noise attacks, number of pixels changing rate (NPCR), unified average change intensity randomness (UACI), and others tests were applied to measure the strength of the proposed encryption scheme. The obtained results prove that the proposed scheme is very robust against different cryptography attacks compared to similar encryption schemes.

scholarly journals From Femtoseconds to Hours–Measuring Dynamics over 18 Orders of Magnitude with Coherent X-rays

2021 ◽  
Vol 11 (13) ◽  
pp. 6179
Author(s):  
Felix Lehmkühler ◽  
Wojciech Roseker ◽  
Gerhard Grübel
Keyword(s):  
Time Scales ◽  
Free Electron Laser ◽  
Photon Correlation Spectroscopy ◽  
Signal To Noise Ratio ◽  
Coherent Scattering ◽  
Correlation Spectroscopy ◽  
X Rays ◽  
Photon Correlation ◽  
X Ray ◽  
Scattering Technique

X-ray photon correlation spectroscopy (XPCS) enables the study of sample dynamics between micrometer and atomic length scales. As a coherent scattering technique, it benefits from the increased brilliance of the next-generation synchrotron radiation and Free-Electron Laser (FEL) sources. In this article, we will introduce the XPCS concepts and review the latest developments of XPCS with special attention on the extension of accessible time scales to sub-μs and the application of XPCS at FELs. Furthermore, we will discuss future opportunities of XPCS and the related technique X-ray speckle visibility spectroscopy (XSVS) at new X-ray sources. Due to its particular signal-to-noise ratio, the time scales accessible by XPCS scale with the square of the coherent flux, allowing to dramatically extend its applications. This will soon enable studies over more than 18 orders of magnitude in time by XPCS and XSVS.

scholarly journals Diagnosis of secondary caries in esthetic restorations: influence of the incidence vertical angle of the X-ray beam

2011 ◽  
Vol 22 (2) ◽  
pp. 129-133 ◽  
Author(s):  
Patrícia Lima Moreira ◽  
Michel Reis Messora ◽  
Stela Márcia Pereira ◽  
Solange Maria de Almeida ◽  
Adriana Dibo da Cruz
Keyword(s):  
Interobserver Reliability ◽  
Negative Influence ◽  
Composite Resins ◽  
Wilcoxon Test ◽  
Vertical Angle ◽  
Human Teeth ◽  
Radiographic Images ◽  
Secondary Caries ◽  
X Ray ◽  
Significant Difference

The aim of this study was to evaluate the accuracy on the diagnosis of secondary caries-like lesions simulated on esthetic restorations of different materials, changing the incidence vertical angle (IVA) of the x-ray beam. Twenty human teeth received MOD inlay preparations. In the experimental group (n=10), a round cavity was made in the floor of the proximal box to simulate the caries-like lesion. All teeth were restored with 3 composite resins (Charisma, Filtek-Z250 and TPH-Spectrum) at 3 moments. Two radiographic images were acquired with 0º and 10º IVA. Ten observers evaluated the images using a 5-point confidence scale. Intra- and interobserver reliability was analyzed with the Interclass Correlation Coefficient and the diagnostic accuracy was evaluated using the area under the ROC curve (Az), Friedman test and Wilcoxon test (α=0.05). Higher accuracy values were obtained with 10º IVA (Az=0.66, Filtek-Z250>Az=0.56, TPH-Spectrum) compared to 0º (Az=0.55, Charisma>Az=0.37, TPH-Spectrum), though without statistically significant difference (p>0.05). The detection of secondary caries-like lesions simulated on esthetic restorations of different materials suffered no negative influence by changing the IVA of the x-ray beam.

scholarly journals Detection and Classification of Cancer from Microscopic Biopsy Images Using Clinically Significant and Biologically Interpretable Features

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Rajesh Kumar ◽  
Rajeev Srivastava ◽  
Subodh Srivastava
Keyword(s):  
Texture Features ◽  
Histogram Equalization ◽  
Gray Level ◽  
Segmentation Methods ◽  
Segmented Images ◽  
Clinically Significant ◽  
Classification Of Images ◽  
Nearest Neighborhood ◽  
Neighborhood Method

A framework for automated detection and classification of cancer from microscopic biopsy images using clinically significant and biologically interpretable features is proposed and examined. The various stages involved in the proposed methodology include enhancement of microscopic images, segmentation of background cells, features extraction, and finally the classification. An appropriate and efficient method is employed in each of the design steps of the proposed framework after making a comparative analysis of commonly used method in each category. For highlighting the details of the tissue and structures, the contrast limited adaptive histogram equalization approach is used. For the segmentation of background cells, k-means segmentation algorithm is used because it performs better in comparison to other commonly used segmentation methods. In feature extraction phase, it is proposed to extract various biologically interpretable and clinically significant shapes as well as morphology based features from the segmented images. These include gray level texture features, color based features, color gray level texture features, Law’s Texture Energy based features, Tamura’s features, and wavelet features. Finally, the K-nearest neighborhood method is used for classification of images into normal and cancerous categories because it is performing better in comparison to other commonly used methods for this application. The performance of the proposed framework is evaluated using well-known parameters for four fundamental tissues (connective, epithelial, muscular, and nervous) of randomly selected 1000 microscopic biopsy images.

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