The Experts below are selected from a list of 174 Experts worldwide ranked by ideXlab platform
Gary L Gallia - One of the best experts on this subject based on the ideXlab platform.
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detection of tumor derived dna in cerebrospinal fluid of patients with primary tumors of the brain and spinal cord
Proceedings of the National Academy of Sciences of the United States of America, 2015Co-Authors: Yuxuan Wang, Simeon Springer, Ming Zhang, Wyatt K Mcmahon, Isaac Kinde, Lisa Dobbyn, Janine Ptak, Henry Brem, Kaisorn L Chaichana, Gary L GalliaAbstract:Outcomes for individuals with central nervous system (CNS) malignancies remain abysmal. A major challenge in managing these patients is the lack of reliable biomarkers to monitor tumor dynamics. Consequently, many patients undergo invasive surgical procedures to determine disease status or experience treatment delays when Radiographic Testing fails to show disease progression. We show here that primary CNS malignancies shed detectable levels of tumor DNA into the surrounding cerebrospinal fluid (CSF), which could serve as a sensitive and exquisitely specific marker for quantifying tumor burden without invasive biopsies. Therefore, assessment of such tumor-derived DNA in the CSF has the potential to improve the management of patients with primary CNS tumors.
Domingo Mery - One of the best experts on this subject based on the ideXlab platform.
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the state of the art of weld seam Radiographic Testing part i image processing
Materials evaluation, 2007Co-Authors: Romeu R Da Silva, Domingo MeryAbstract:Over the past 30 years, a large amount of research has been conducted to develop an automatic (or semiautomatic) system for the Radiographic detection and classification of discontinuities in continuous welds. There are two major types of research in this field: image processing, which consists of improving Radiographic image quality and segmenting regions of interest in the images, and pattern recognition, which aims at detecting and classifying the discontinuities segmented in the images. Because of the complexity of the problem of detecting weld discontinuities, a large number of techniques have been investigated in these areas. This paper represents a state of the art report on weld Testing and is divided into separate parts on image processing and pattern recognition. The techniques presented are compared at each basic step of system development for the identification of discontinuities in continuous welds. This part deals with image processing.
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the state of the art of weld seam Radiographic Testing part ii pattern recognition
Materials evaluation, 2007Co-Authors: Romeu R Da Silva, Domingo MeryAbstract:Over the last 30 years, there has been a large amount of research attempting to develop an automatic (or semiautomatic) system for the detection and classification of weld discontinuities in continuous welds examined by radiography. There are basically two large types of research areas in this field: image processing, which consists in improving the quality of Radiographic images and segmenting regions of interest in the images, and pattern recognition, which aims at detecting and classifying the discontinuities segmented in the images. Because of the complexity of the problem of detecting weld discontinuities, a large number of techniques have been investigated in these areas. This paper represents a state of the art report on weld Testing and is divided into the two parts mentioned above: image processing and pattern recognition. The techniques presented are compared at each basic step of the development of the system for the identification of discontinuities in continuous welds. The first part of this paper (included in the June issue of this journal) dealt with image processing. This part deals with pattern recognition.
Nafaa Nacereddine - One of the best experts on this subject based on the ideXlab platform.
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hybrid shape descriptors for an improved weld defect retrieval in Radiographic Testing
Soft Computing, 2015Co-Authors: Nafaa Nacereddine, Djemel ZiouAbstract:In this paper, four region-based shape descriptors well reported in the literature are used to characterize weld defect types of crack, lack of penetration, porosity and solid inclusion, usually encountered in Radiographic Testing of welds. The rectangularity and the roundness in the geometric descriptor (GEO) are used in order to propose an hybridization algorithm so that the hybrid descriptor issued from GEO and each of the other descriptors becomes more discriminant in such application where, due to bad Radiographic image quality and weld defect typology, the human film interpretation is often inconsistent and labor intensive. According to the results given in the experiments, the efficiency of the proposed hybrid descriptors is confirmed on the weld defects mentioned above where, the retrieval scores are significantly improved compared to the original descriptors used separately.
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Image Thresholding for Weld Defect Extraction in Industrial Radiographic Testing
World Academy of Science Engineering and Technology International Journal of Computer Electrical Automation Control and Information Engineering, 2007Co-Authors: Nafaa Nacereddine, Latifa Hamami, Djemel ZiouAbstract:In non destructive Testing by radiography, a perfect knowledge of the weld defect shape is an essential step to appreciate the quality of the weld and make decision on its acceptability or rejection. Because of the complex nature of the considered images, and in order that the detected defect region represents the most accurately possible the real defect, the choice of thresholding methods must be done judiciously. In this paper, performance criteria are used to conduct a comparative study of thresholding methods based on gray level histogram, 2-D histogram and locally adaptive approach for weld defect extraction in Radiographic images.
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parametric active contour for weld defects boundary extraction in Radiographic Testing
Eighth International Conference on Quality Control by Artificial Vision, 2007Co-Authors: Aicha Baya Goumeidane, Nafaa Nacereddine, Mohammed Khamadja, F MekhalfaAbstract:Snakes, or active contours, are used extensively in computer vision and image processing applications, particularly to locate object boundaries. Problems associated with initialization and poor convergences to boundary concavities have aroused, which restricts their utility. This paper presents a new approach to deal with the defects contours estimation problem in Radiographic images using parametric active contours. In this approach we exploit the performance of the GVF as external force and enhance it by joining to it an external adaptive pressure forces which speeds up to the snake progression, makes it less sensitive to initialization and provides capability of tracking the concavities.
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thresholding techniques and their performance evaluation for weld defect detection in Radiographic Testing
International Conference on Computer Vision and Graphics, 2006Co-Authors: Nafaa Nacereddine, Latifa Hamami, Djemel ZiouAbstract:In non-destructive Testing with radiography, a perfect knowledge of the weld defect shape is an essential step to appreciate the quality of the weld and make decision on its acceptance or rejection. Because of the complex nature of the considered images, and in order that the detected defect region represent the real defect as accurately as possible, the choice of the thresholding methods must be made judiciously. In this paper, performance criteria are used to conduct a comparative study of the thresholding methods based on the gray level histogram, the 2D histogram and the locally adaptive approach to weld defect detection in Radiographic images.
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statistical tools for weld defect evaluation in Radiographic Testing
2006Co-Authors: Nafaa Nacereddine, Latifa Hamami, Dp Electronique, Djemel ZiouAbstract:A reliable detection of defects in welded joints is one of the most important tasks in non-destructive Testing by radiography, since the human factor still has a decisive influence on the evaluation of defects on the film. An incorrect classification may disapprove a piece in good conditions or approve a piece with discontinuities exceeding the limit established by the applicable standards. The progresses in computer science and the artificial intelligence techniques have allowed the welded joint quality interpretation to be carried out by using pattern recognition tools, making the system of the weld inspection more reliable, reproducible and faster. In this work, we develop and implement algorithms based on statistical approaches for segmentation and classification of the weld defects. Because of the complex nature of the considered images and so that the extracted defect area represents the most accurately possible the real defect, and that the detected defect corresponds as well as possible to its real class, the choice of the algorithms must be very judicious. In order to achieve this, a comparative study of the various segmentation and classification methods was performed to demonstrate the advantages of the ones in comparison with the others giving to the most optimal combinations.
V I Kapusti - One of the best experts on this subject based on the ideXlab platform.
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classification of defects in computerized Radiographic Testing of welds
Russian Journal of Nondestructive Testing, 2009Co-Authors: S A Grigorchenko, V I KapustiAbstract:A technique of classifying images of defects in automatic Radiographic Testing of welds is presented. A mathematical description of images of defects is given. A heuristic classifier developed with allowance for generalization of the experience of industrial radiography and implemented in software and hardware complexes of computerized coding of radiographs (CCCR) is considered.
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development of the main requirements for contemporary systems of Radiographic Testing including digital image processing taking into account specific features of inspection of welded joints of oil and gas pipelines a review
Russian Journal of Nondestructive Testing, 2008Co-Authors: E A Alekhnovich, V I Kapusti, N E Vankova, A I Karpenko, T N MaksimovaAbstract:Contemporary Radiographic systems with digital image processing for Testing welded joints of oil and gas pipelines are analyzed. The main requirements for systems for computer interpretation and archiving of Radiographic images and personnel interpreting radiograms are formulated.
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main trends of standardization of the Radiographic Testing method
Russian Journal of Nondestructive Testing, 2001Co-Authors: V I Kapusti, T N Maksimova, V G Staseev, V G FirstovAbstract:Corrected general and methodical requirements to the method, technology, and instrumentation of Radiographic Testing which reflect the modern level of the development of nondestructive Testing methods and radiation technique are established. Existing standards are analyzed to determine their degree of correspondence to the work under market conditions. Promising and priority trends in the field of standardization of Radiographic Testing method are determined. Ways for bringing the Russian standards in accordance with the international ones are proposed for approaches to the Radiographic Testing technique and technology and the Testing and measurement instrumentations.
Djemel Ziou - One of the best experts on this subject based on the ideXlab platform.
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hybrid shape descriptors for an improved weld defect retrieval in Radiographic Testing
Soft Computing, 2015Co-Authors: Nafaa Nacereddine, Djemel ZiouAbstract:In this paper, four region-based shape descriptors well reported in the literature are used to characterize weld defect types of crack, lack of penetration, porosity and solid inclusion, usually encountered in Radiographic Testing of welds. The rectangularity and the roundness in the geometric descriptor (GEO) are used in order to propose an hybridization algorithm so that the hybrid descriptor issued from GEO and each of the other descriptors becomes more discriminant in such application where, due to bad Radiographic image quality and weld defect typology, the human film interpretation is often inconsistent and labor intensive. According to the results given in the experiments, the efficiency of the proposed hybrid descriptors is confirmed on the weld defects mentioned above where, the retrieval scores are significantly improved compared to the original descriptors used separately.
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Image Thresholding for Weld Defect Extraction in Industrial Radiographic Testing
World Academy of Science Engineering and Technology International Journal of Computer Electrical Automation Control and Information Engineering, 2007Co-Authors: Nafaa Nacereddine, Latifa Hamami, Djemel ZiouAbstract:In non destructive Testing by radiography, a perfect knowledge of the weld defect shape is an essential step to appreciate the quality of the weld and make decision on its acceptability or rejection. Because of the complex nature of the considered images, and in order that the detected defect region represents the most accurately possible the real defect, the choice of thresholding methods must be done judiciously. In this paper, performance criteria are used to conduct a comparative study of thresholding methods based on gray level histogram, 2-D histogram and locally adaptive approach for weld defect extraction in Radiographic images.
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thresholding techniques and their performance evaluation for weld defect detection in Radiographic Testing
International Conference on Computer Vision and Graphics, 2006Co-Authors: Nafaa Nacereddine, Latifa Hamami, Djemel ZiouAbstract:In non-destructive Testing with radiography, a perfect knowledge of the weld defect shape is an essential step to appreciate the quality of the weld and make decision on its acceptance or rejection. Because of the complex nature of the considered images, and in order that the detected defect region represent the real defect as accurately as possible, the choice of the thresholding methods must be made judiciously. In this paper, performance criteria are used to conduct a comparative study of the thresholding methods based on the gray level histogram, the 2D histogram and the locally adaptive approach to weld defect detection in Radiographic images.
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statistical tools for weld defect evaluation in Radiographic Testing
2006Co-Authors: Nafaa Nacereddine, Latifa Hamami, Dp Electronique, Djemel ZiouAbstract:A reliable detection of defects in welded joints is one of the most important tasks in non-destructive Testing by radiography, since the human factor still has a decisive influence on the evaluation of defects on the film. An incorrect classification may disapprove a piece in good conditions or approve a piece with discontinuities exceeding the limit established by the applicable standards. The progresses in computer science and the artificial intelligence techniques have allowed the welded joint quality interpretation to be carried out by using pattern recognition tools, making the system of the weld inspection more reliable, reproducible and faster. In this work, we develop and implement algorithms based on statistical approaches for segmentation and classification of the weld defects. Because of the complex nature of the considered images and so that the extracted defect area represents the most accurately possible the real defect, and that the detected defect corresponds as well as possible to its real class, the choice of the algorithms must be very judicious. In order to achieve this, a comparative study of the various segmentation and classification methods was performed to demonstrate the advantages of the ones in comparison with the others giving to the most optimal combinations.