scholarly journals Overview of Segmentation X-Ray Medical Images Using Image Processing Technique

2020 ◽  
Vol 1529 ◽  
pp. 042017
Author(s):  
Wan Azani Mustafa ◽  
Nurshahira Mohd Salleh ◽  
Syed Zulkarnain Syed Idrus ◽  
Mohd Aminudin Jamlos ◽  
Mohamad Nur Khairul Hafizi Rohani
Keyword(s):  
Image Processing ◽  
Medical Images ◽  
Processing Technique ◽  
Image Processing Technique ◽  
X Ray

An image processing technique for the identification of contact pixels applied to X-ray CT images of implanted hip prostheses

1993 ◽  
Vol 38 (2) ◽  
pp. 323-328 ◽  
Author(s):  
E Berry ◽  
V G Langkamer ◽  
P C Jackson ◽  
M Snow ◽  
P R Goddard ◽  
...  
Keyword(s):  
Image Processing ◽  
Processing Technique ◽  
Ct Images ◽  
Image Processing Technique ◽  
Hip Prostheses ◽  
X Ray

A study on quality improvement of x-ray imaging of the respiratory-system based on a new image processing technique

2015 ◽  
Author(s):  
Jun Torii ◽  
Yuichi Nagai ◽  
Tatsuya Horita ◽  
Yuuji Matsumoto ◽  
Takehiro Izumo ◽  
...  
Keyword(s):  
Image Processing ◽  
Quality Improvement ◽  
Respiratory System ◽  
Processing Technique ◽  
Image Processing Technique ◽  
X Ray ◽  
X Ray Imaging

scholarly journals Leg Bone Fracture Segmentation and Detection using Advanced Morphological Techniques

2019 ◽  
Vol 8 (2S3) ◽  
pp. 1246-1249 ◽  
Keyword(s):  
Image Processing ◽  
Bone Fracture ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Bone Area ◽  
Fracture Detection ◽  
Statistical Parameters ◽  
Accurate Identification ◽  
X Ray ◽  
Vehicle Accidents

The bone fracture is the most common problem and is likely to occur due to traumatic incidents like vehicle accidents, sporting injuries or due to conditions like osteoporosis, cancer related to bones. Fracture cannot be viewed by naked eye and so X-ray, CT, ultrasound, MRI images are used to detect it. These images cannot be diagnosed directly and henceforth image processing plays a very important role in fracture detection. This paper presents an image processing technique that uses Laplacian method of edge detection for accurate identification of fractured bone area from the X-ray/CT images. From the fractured bone area several parameters like mean, standard deviation are calculated in order to analyze the accuracy and sensitivity of the used technique. NIVISION assistant software is used and the statistical parameters are calculated.

Jaya Algorithm-Assisted Evaluation of Tooth Elements Using Digital Bitewing Radiography Images

2019 ◽  
pp. 107-128 ◽  
Author(s):  
Kesavan Suresh Manic ◽  
Imad Saud Al Naimi ◽  
Feras N. Hasoon ◽  
V. Rajinikanth
Keyword(s):  
Image Processing ◽  
Ground Truth ◽  
Processing Technique ◽  
Automated Detection ◽  
Image Processing Technique ◽  
Evaluation Procedure ◽  
Jaya Algorithm ◽  
X Ray ◽  
Bitewing Radiography ◽  
Heuristic Procedures

A considerable number of heuristic procedures are widely implemented to evaluate biomedical images. This chapter proposes an evaluation procedure for digital bitewing radiography (DBR) images using the Jaya algorithm. The proposed procedure implements an image processing technique by integrating of the multi-thresholding and segmentation procedure to extract the essential tooth elements recorded with DBR. In this paper, 80 dental x-ray images are considered for the evaluation. The performance of the proposed procedure is confirmed using a relative assessment between the extracted section and its corresponding ground-truth. The results of this study confirm that, for most of the DBR cases, the proposed approach offers better values of picture likeliness measures. Hence, this technique can be considered for the automated detection of tooth elements from the DBR obtained from clinics.

scholarly journals Locating the 'missing wedge' artifacts from limited-angle CT reconstruction

2018 ◽  
Vol 24 (S2) ◽  
pp. 140-141
Author(s):  
Jianhong Liu ◽  
Yong Guan ◽  
Liang Chen ◽  
Haobo Bai ◽  
Wenbin Wei ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Image Processing ◽  
Image Analysis ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Ct Image ◽  
Ct Reconstruction ◽  
Reconstruction Algorithms ◽  
X Ray ◽  
Reconstruction Quality

Abstract:'Missing wedge' problem exists in some kind of CT imaging situations, such as electron microscopy, x-ray nano-CT image, etc. Method such as iterative reconstruction algorithms, total variation based method were applied to improve the reconstruction quality, but the 'missing wedge' artifacts are still inevitable. In this paper, a method based on image processing technique was proposed to locate the 'missing wedge' artifacts in CT reconstruction. The result showed good performance on locating the artifacts, which also showed the potential in CT reconstruction and image analysis in nano-CT.

scholarly journals Applying Computed Tomography (CT) scanning for segmentation of permafrost constituents in drill cores

2021 ◽  
Author(s):  
Damir Gadylyaev ◽  
Jan Nitzbon ◽  
Steffen Schlüter ◽  
John Maximilian Köhne ◽  
Guido Grosse ◽  
...  
Keyword(s):  
Image Processing ◽  
Volume Fraction ◽  
Ice Cores ◽  
Ct Scanning ◽  
Processing Technique ◽  
Laboratory Analysis ◽  
Image Processing Technique ◽  
X Ray ◽  
Ice Content ◽  
Non Destructive

<p>Computed X-ray Tomography is a non-destructive technique that allows three-dimensional imaging of soil samples' internal structures, determined by variations in their density and atomic composition. This study's objective was to develop an image processing workflow for the quantitative analysis of ice cores using high-resolution CT in order to determine the volume fraction and vertical distribution of ice, mineral, gas, and organic matter in permafrost cores. We analyzed a 155 cm permafrost core taken from a Yedoma permafrost upland on Kurungnakh Island in the Lena River Delta (northeast Siberia). The obtained results were evaluated and compared with the results of detailed, but sample-destructive laboratory analysis. The frozen permafrost core was subjected to a computerized X-ray imaging procedure with a resolution of 50 micrometers. As a result, we obtained 31000 images. Noise in the raw images is removed with a non-local means denoising filter. We chose multilevel thresholding method for the image segmentation step. Threshold values were determined based on the histograms of the images. We measured the volumetric ice content (VIC) using Java-based image processing software (ImageJ). In addition, the vertical profiles were analyzed in 1-2cm intervals. We received bulk densities and VIC by freeze-drying and standard laboratory analysis. From the top of the core and until roughly 86 cm, it mainly consists of ice and organic, with an average of 67% and 30% results, respectively. The rest of the volume is divided almost equally between air and mineral parts. Below 86 cm, it consists almost entirely of pure ice. The ice content constitutes around 97% of the composition, and air rises to roughly 3%, while mineral and organic are almost equal to zero. The difference between VIC derived through CT scan and laboratory-derived VIC lies within the range of -37% to 25%. However, the vast majority of values lie within the range of -10% to 10%. This image processing technique to quantify VIC provides a non-destructive analog to traditional laboratory analysis that could help increasing the vertical resolution for quantifying mineral, ice, gas, and organic components in permafrost cores as well as enhance the volumetric estimate.</p>

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