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Journal articles on the topic 'Medical in art Radiography'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Yahaghi, Effat, Amir Movafeghi, Shokoofeh Ahmadi, Sholeh Ansari, Mehran Taheri, and Naser Rastkhah. "Cultural Heritage Object Identification by Radiography Nondestructive Method and Digital Image Processing." Applied Mechanics and Materials 83 (July 2011): 35–40. http://dx.doi.org/10.4028/www.scientific.net/amm.83.35.

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Nondestructive testing (NDT) is an important tool in the world of industry. Among different NDT methods, radiography plays a very interesting role both in industry and medicine. Medical and industrial uses of X and gamma rays were recognized since more than 1 century ago. One of the interesting uses of radiography is in archeological and art applications. In this research, radiography was utilized for identification of a damaged art-historical material. The subject is a brass tray belonging to Iran cultural heritage with an estimated age of about 3500 years. The tray was found in Lorestan province and referred to as “Lorestan bonze”. The object was damaged seriously due to heavy corrosion attack. Therefore recognition of the object was a major problem. Normal radiography method can help for object determination, but it suffers some major drawbacks related to contrast and thickness measurement. Image processing technique and a precise thickness measurement method were added to digitized radiographs. A precise radiographic thickness method was introduced and used before for the pipeline radiography. For digital image processing, Canny edge detection method and Gaussian filter were used. Radiography image obtained from this work showed a very clear picture of the original trace of hammered design. These results showed that a combination of radiography, image processing techniques and consideration of physical principles of radiation interaction with materials can produce a very clear image which can be used effectively for hte detail analysis of cultural heritages.

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2

Meier, Reinhard, Christian Krug, Daniel Golovko, Sophie Boddington, Guido Piontek, Martina Rudelius, Elizabeth J. Sutton, Andrea Baur-Melnyk, Ella F. Jones, and Heike E. Daldrup-Link. "Indocyanine green-enhanced imaging of antigen-induced arthritis with an integrated optical imaging/radiography system." Arthritis & Rheumatism 62, no. 8 (May 5, 2010): 2322–27. http://dx.doi.org/10.1002/art.27542.

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3

Carr, Christopher, and Jean-Christophe Komorowski. "Identifying the Mineralogy of Rock Temper in Ceramics Using X-Radiography." American Antiquity 60, no. 4 (October 1995): 723–49. http://dx.doi.org/10.2307/282055.

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Industrial and medical x-radiography can be used in a manner analogous to back-scattered electron microscopy to identify the approximate mineralogy of rock temper particles in ceramics, but without their destruction by thin-sectioning, and at low cost. Particle traits similar to those used in petrography to identify a mineral are visible in a magnified x-radiograph. The traits include particle x-radiographic gray level, which varies with a particle’s mean atomic number, specific gravity, and mineralogy; size; morphology; cleavage; and internal texture. Blind tests are made to evaluate the specificity and accuracy of the method. Its utility is shown through a study of the exchange of Ohio Middle Woodland ceramics.

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4

Malattia, Clara, Maria Beatrice Damasio, Francesca Magnaguagno, Angela Pistorio, Maura Valle, Carlo Martinoli, Stefania Viola, et al. "Magnetic resonance imaging, ultrasonography, and conventional radiography in the assessment of bone erosions in juvenile idiopathic arthritis." Arthritis & Rheumatism 59, no. 12 (December 15, 2008): 1764–72. http://dx.doi.org/10.1002/art.24313.

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5

Hauzeur, Jean-Philippe, and Valérie Gangji. "Early Kienböck disease cannot be detected by radiography: Comment on the clinical image by Ko et al." Arthritis & Rheumatism 62, no. 4 (January 28, 2010): 1201. http://dx.doi.org/10.1002/art.27341.

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6

Nevitt, Michael C., Charles Peterfy, Ali Guermazi, David T. Felson, Jeff Duryea, Thasia Woodworth, Hepei Chen, Kent Kwoh, and Tamara B. Harris. "Longitudinal performance evaluation and validation of fixed-flexion radiography of the knee for detection of joint space loss." Arthritis & Rheumatism 56, no. 5 (2007): 1512–20. http://dx.doi.org/10.1002/art.22557.

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7

Brandt, Kenneth D. "Translating osteoarthritis into numbers: The importance of alignment in knee radiography for clinical trials of structure-modifying drugs." Arthritis & Rheumatism 52, no. 5 (May 2005): 1343–45. http://dx.doi.org/10.1002/art.21025.

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8

Issa, Sakeba N., Dorothy Dunlop, Alison Chang, Jing Song, Pottumarthi V. Prasad, Ali Guermazi, Charles Peterfy, et al. "Full-limb and knee radiography assessments of varus-valgus alignment and their relationship to osteoarthritis disease features by magnetic resonance imaging." Arthritis & Rheumatism 57, no. 3 (2007): 398–406. http://dx.doi.org/10.1002/art.22618.

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9

van Rossum, Marion A. J., Maarten Boers, Aeilko H. Zwinderman, Renée M. van Soesbergen, Helen Wieringa, Theo J. W. Fiselier, Marcel J. A. M. Franssen, et al. "Development of a standardized method of assessment of radiographs and radiographic change in juvenile idiopathic arthritis: Introduction of the Dijkstra composite score." Arthritis & Rheumatism 52, no. 9 (2005): 2865–72. http://dx.doi.org/10.1002/art.21247.

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10

Ho, Thi Kieu, and Jeonghwan Gwak. "Multiple Feature Integration for Classification of Thoracic Disease in Chest Radiography." Applied Sciences 9, no. 19 (October 2, 2019): 4130. http://dx.doi.org/10.3390/app9194130.

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The accurate localization and classification of lung abnormalities from radiological images are important for clinical diagnosis and treatment strategies. However, multilabel classification, wherein medical images are interpreted to point out multiple existing or suspected pathologies, presents practical constraints. Building a highly precise classification model typically requires a huge number of images manually annotated with labels and finding masks that are expensive to acquire in practice. To address this intrinsically weakly supervised learning problem, we present the integration of different features extracted from shallow handcrafted techniques and a pretrained deep CNN model. The model consists of two main approaches: a localization approach that concentrates adaptively on the pathologically abnormal regions utilizing pretrained DenseNet-121 and a classification approach that integrates four types of local and deep features extracted respectively from SIFT, GIST, LBP, and HOG, and convolutional CNN features. We demonstrate that our approaches efficiently leverage interdependencies among target annotations and establish the state of the art classification results of 14 thoracic diseases in comparison with current reference baselines on the publicly available ChestX-ray14 dataset.

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11

Bird, Paul, Bruce Kirkham, Ian Portek, Ron Shnier, Fredrick Joshua, John Edmonds, and Marissa Lassere. "Documenting damage progression in a two-year longitudinal study of rheumatoid arthritis patients with established disease (the DAMAGE study cohort): Is there an advantage in the use of magnetic resonance imaging as compared with plain radiography?" Arthritis & Rheumatism 50, no. 5 (2004): 1383–89. http://dx.doi.org/10.1002/art.20165.

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12

Magni-Manzoni, Silvia, Federica Rossi, Angela Pistorio, Francesca Temporini, Stefania Viola, Giampiero Beluffi, Alberto Martini, and Angelo Ravelli. "Prognostic factors for radiographic progression, radiographic damage, and disability in juvenile idiopathic arthritis." Arthritis & Rheumatism 48, no. 12 (December 2003): 3509–17. http://dx.doi.org/10.1002/art.11337.

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13

Deyo, Richard A., Lawrence M. McNiesh, and Robert O. Cone. "Observer variability in the interpretation of lumbar spine radiographs." Arthritis & Rheumatism 28, no. 9 (September 1985): 1066–70. http://dx.doi.org/10.1002/art.1780280916.

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14

Gardner, Gregory C., and John C. Hunter. "Clinical images: Radiographic healing of osseous sarcoidosis." Arthritis & Rheumatism 52, no. 7 (2005): 2225. http://dx.doi.org/10.1002/art.21102.

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15

James, Michael F., Geoff Heald, John H. Shorter, and Robert A. Turner. "Joint space measurement in hand radiographs using computerized image analysis." Arthritis & Rheumatism 38, no. 7 (July 1995): 891–901. http://dx.doi.org/10.1002/art.1780380704.

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16

Brower, Anne C. "Use of the radiograph to measure the course of rheumatoid arthritis." Arthritis & Rheumatism 33, no. 3 (March 1990): 316–24. http://dx.doi.org/10.1002/art.1780330303.

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17

Dahaghin, S., S. M. A. Bierma-zeinstra, J. M. W. Hazes, and B. W. Koes. "Clinical burden of radiographic hand osteoarthritis: A systematic appraisal." Arthritis & Rheumatism 55, no. 4 (2006): 636–47. http://dx.doi.org/10.1002/art.22109.

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18

Dalbeth, Nicola, Barnaby Clark, Fiona McQueen, Anthony Doyle, and William Taylor. "Validation of a radiographic damage index in chronic gout." Arthritis & Rheumatism 57, no. 6 (2007): 1067–73. http://dx.doi.org/10.1002/art.22891.

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19

Axford, J. S., P. Revell, I. Watt, A. Bomford, R. Williams, and E. B. D. Hamilton. "Hip arthropathy in genetic hemochromatosis. Radiographic and histologic features." Arthritis & Rheumatism 34, no. 3 (March 1991): 357–61. http://dx.doi.org/10.1002/art.1780340314.

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20

Nevitt, Michael C., Nancy E. Lane, Jean C. Scott, Marc C. Hochberg, Alice R. Pressman, Harry K. Genant, and Steven R. Cummings. "Radiographic osteoarthritis of the hip and bone mineral density." Arthritis & Rheumatism 38, no. 7 (July 1995): 907–16. http://dx.doi.org/10.1002/art.1780380706.

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21

Goronzy, J�rg J., Eric L. Matteson, James W. Fulbright, Kenneth J. Warrington, April Chang-Miller, Gene G. Hunder, Thomas G. Mason, et al. "Prognostic markers of radiographic progression in early rheumatoid arthritis." Arthritis & Rheumatism 50, no. 1 (January 2004): 43–54. http://dx.doi.org/10.1002/art.11445.

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22

Maharjan, Surendra. "Radiation knowledge among radiographers and radiography students." Radiography Open 3, no. 1 (April 1, 2017): 17. http://dx.doi.org/10.7577/radopen.2000.

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Objective To evaluate the knowledge of radiation among radiographers and radiography students in NepalMethods A validated questionnaire was conducted among radiographers and radiography students in 24th annual meeting and workshop of Nepal Radiological Society (NRS) on 10th September, 2015. The survey included multiple choice questions (MCQs) related to demographic characteristics (age, gender), academic qualification, work experience and knowledge of radiation. The data were analyzed using SPSS software version 21.0.Results Of total 102 respondents, 68.6% (70) were students and 31.4% (32) were radiographers. There were 65 male and 37 female with age ranging from 18 to 45, mean 23.70±5.11 years. Out of 14 MCQs related to knowledge of radiation, maximum score was 14 and minimum 5 with mean 9.99±1.94 (mean percentage 71.35%) (radiographers 10.63±2.10, 75.89% and students 9.70±1.80, 69.28%) respectively. Most participants failed in questions related to radiation units, minimum safe distance during portable radiography, fluoroscopy, and cancer risk of chest radiograph.Conclusion Overall awareness and knowledge of radiation was satisfying with definite possibilities for further improvement through regular trainings, workshops and continuing medical education (CME) programs related to radiation protection and safety. Furthermore, it is an urgent requirement of national radiation protection act in Nepal

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23

Isomäuki, Heikki, Kalevi Kaarela, and Jukka Martio. "Are hand radiographs the most suitable for the diagnosis of rheumatoid arthritis?" Arthritis & Rheumatism 31, no. 11 (November 1988): 1452–53. http://dx.doi.org/10.1002/art.1780311120.

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24

Niu, J., Y. Q. Zhang, J. Torner, M. Nevitt, C. E. Lewis, P. Aliabadi, B. Sack, M. Clancy, L. Sharma, and D. T. Felson. "Is obesity a risk factor for progressive radiographic knee osteoarthritis?" Arthritis & Rheumatism 61, no. 3 (March 15, 2009): 329–35. http://dx.doi.org/10.1002/art.24337.

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25

Arden, Nigel K., Nancy E. Lane, Neeta Parimi, Kassim M. Javaid, Li-Yung Lui, Marc C. Hochberg, and Michael Nevitt. "Defining incident radiographic hip osteoarthritis for epidemiologic studies in women." Arthritis & Rheumatism 60, no. 4 (April 2009): 1052–59. http://dx.doi.org/10.1002/art.24382.

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26

Rho, Young Hee, Joseph Solus, Tuulikki Sokka, Annette Oeser, Cecilia P. Chung, Tebeb Gebretsadik, Ayumi Shintani, Theodore Pincus, and C. Michael Stein. "Adipocytokines are associated with radiographic joint damage in rheumatoid arthritis." Arthritis & Rheumatism 60, no. 7 (July 2009): 1906–14. http://dx.doi.org/10.1002/art.24626.

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27

Hannan, Marian T., David T. Felson, Jennifer J. Anderson, Allan Naimark, and William B. Kannel. "Estrogen use and radiographic osteoarthritis of the knee in women." Arthritis & Rheumatism 33, no. 4 (April 1990): 525–32. http://dx.doi.org/10.1002/art.1780330410.

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28

Khan, Muhammad Asim. "Delay in the radiographic detection of sacroitiitis in ankylosing spondylitis." Arthritis & Rheumatism 35, no. 6 (June 1992): 727. http://dx.doi.org/10.1002/art.1780350623.

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29

Le Graverand, M.-P. Hellio, R. J. Buck, B. T. Wyman, E. Vignon, S. A. Mazzuca, K. D. Brandt, M. Piperno, et al. "Change in regional cartilage morphology and joint space width in osteoarthritis participants versus healthy controls: a multicentre study using 3.0 Tesla MRI and Lyon–Schuss radiography." Annals of the Rheumatic Diseases 69, no. 01 (December 22, 2008): 155–62. http://dx.doi.org/10.1136/ard.2008.099762.

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Objective:Cartilage morphology displays sensitivity to change in osteoarthritis (OA) with quantitative MRI (qMRI). However, (sub)regional cartilage thickness change at 3.0 Tesla (T) has not been directly compared with radiographic progression of joint space narrowing in OA participants and non-arthritic controls.Methods:A total of 145 women were imaged at 7 clinical centres: 86 were non-obese and asymptomatic without radiographic OA and 55 were obese with symptomatic and radiographic OA (27 Kellgren–Lawrence grade (KLG)2 and 28 KLG3). Lyon–Schuss (LS) and fixed flexion (FF) radiographs were obtained at baseline, 12 and 24 months, and coronal spoiled gradient echo MRI sequences at 3.0 T at baseline, 6, 12 and 24 months. (Sub)regional, femorotibial cartilage thickness and minimum joint space width (mJSW) in the medial femorotibial compartment were measured and the standardised response means (SRMs) determined.Results:At 6 months, qMRI demonstrated a −3.7% “annualised” change in cartilage thickness (SRM −0.33) in the central medial femorotibial compartment (cMFTC) of KLG3 subjects, but no change in KLG2 subjects. The SRM for mJSW in 12-month LS/FF radiographs of KLG3 participants was −0.68/−0.13 and at 24 months was −0.62/−0.20. The SRM for cMFTC changes measured with qMRI was −0.32 (12 months; −2.0%) and −0.48 (24 months; −2.2%), respectively.Conclusions:qMRI and LS radiography detected significant change in KLG3 participants at high risk of progression, but not in KLG2 participants, and only small changes in controls. At 12 and 24 months, LS displayed greater, and FF less, sensitivity to change in KLG3 participants than qMRI.

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30

Dieppe, Paul A., Stephan Reichenbach, Susan Williams, Paul Gregg, Iain Watt, and Peter Jüni. "Assessing bone loss on radiographs of the knee in osteoarthritis: A cross-sectional study." Arthritis & Rheumatism 52, no. 11 (2005): 3536–41. http://dx.doi.org/10.1002/art.21418.

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31

Mazzuca, Steven A., Kenneth D. Brandt, Kathleen A. Lane, and Barry P. Katz. "Knee pain reduces joint space width in conventional standing anteroposterior radiographs of osteoarthritic knees." Arthritis & Rheumatism 46, no. 5 (May 2002): 1223–27. http://dx.doi.org/10.1002/art.10256.

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32

Ward, Michael M., Matthew R. Hendrey, James D. Malley, Thomas J. Learch, John C. Davis, John D. Reveille, and Michael H. Weisman. "Clinical and immunogenetic prognostic factors for radiographic severity in ankylosing spondylitis." Arthritis & Rheumatism 61, no. 7 (July 15, 2009): 859–66. http://dx.doi.org/10.1002/art.24585.

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33

Tornero, J., S. Castaneda, J. Vidal, and G. Herrero-Beaumont. "Differences between radiographic abnormalities of acromegalic arthropathy and those of osteoarthritis." Arthritis & Rheumatism 33, no. 3 (March 1990): 455–56. http://dx.doi.org/10.1002/art.1780330332.

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34

Hoy, Marina D. Sew, John L. O'Donnell, Peter W. Moller, Douglas Kallman, William W. Scott, Marc C. Hochberg, Fredrick M. Wigley, and Jordan D. Tobin. "Comment on the radiographic grading scales for osteoarthritis of the hand." Arthritis & Rheumatism 34, no. 5 (May 1991): 639. http://dx.doi.org/10.1002/art.1780340519.

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35

Klein-Wieringa, Inge R., Michael P. M. van der Linden, Rachel Knevel, Joanneke C. Kwekkeboom, Els van Beelen, Tom W. J. Huizinga, Annette van der Helm-van Mil, Margreet Kloppenburg, René E. M. Toes, and Andreea Ioan-Facsinay. "Baseline serum adipokine levels predict radiographic progression in early rheumatoid arthritis." Arthritis & Rheumatism 63, no. 9 (August 31, 2011): 2567–74. http://dx.doi.org/10.1002/art.30449.

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36

Yazici, Yusuf, and Hasan Yazici. "Trial of etanercept and methotrexate with radiographic and patient outcomes two-year clinical and radiographic results: Comment on the article by van der Heijde et al." Arthritis & Rheumatism 54, no. 9 (2006): 3061–62. http://dx.doi.org/10.1002/art.22121.

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37

Möller, Burkhard, Harald Bonel, Marianne Rotzetter, Peter M. Villiger, and Hans-rudolf Ziswiler. "Measuring finger joint cartilage by ultrasound as a promising alternative to conventional radiograph imaging." Arthritis & Rheumatism 61, no. 4 (April 15, 2009): 435–41. http://dx.doi.org/10.1002/art.24424.

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38

Livieris, Ioannis, Andreas Kanavos, Vassilis Tampakas, and Panagiotis Pintelas. "A Weighted Voting Ensemble Self-Labeled Algorithm for the Detection of Lung Abnormalities from X-Rays." Algorithms 12, no. 3 (March 16, 2019): 64. http://dx.doi.org/10.3390/a12030064.

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During the last decades, intensive efforts have been devoted to the extraction of useful knowledge from large volumes of medical data employing advanced machine learning and data mining techniques. Advances in digital chest radiography have enabled research and medical centers to accumulate large repositories of classified (labeled) images and mostly of unclassified (unlabeled) images from human experts. Machine learning methods such as semi-supervised learning algorithms have been proposed as a new direction to address the problem of shortage of available labeled data, by exploiting the explicit classification information of labeled data with the information hidden in the unlabeled data. In the present work, we propose a new ensemble semi-supervised learning algorithm for the classification of lung abnormalities from chest X-rays based on a new weighted voting scheme. The proposed algorithm assigns a vector of weights on each component classifier of the ensemble based on its accuracy on each class. Our numerical experiments illustrate the efficiency of the proposed ensemble methodology against other state-of-the-art classification methods.

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39

Szebenyi, Béla, Anthony P. Hollander, Paul Dieppe, Brian Quilty, John Duddy, Shane Clarke, and John R. Kirwan. "Associations between pain, function, and radiographic features in osteoarthritis of the knee." Arthritis & Rheumatism 54, no. 1 (2005): 230–35. http://dx.doi.org/10.1002/art.21534.

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40

Mccarthy, Geraldine M., Carl R. Barthelemy, Judith A. Veum, and Robert L. Wortmann. "Influence of antihyperuricemic therapy on the clinical and radiographic progression of gout." Arthritis & Rheumatism 34, no. 12 (August 26, 2010): 1489–94. http://dx.doi.org/10.1002/art.1780341203.

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41

Olivieri, Ignazio, Angela Padula, Vincenzo Giasi, and Enrico Scarano. "Enthesitis of spondylarthritis can masquerade as Osgood-Schlatter disease by radiographic findings." Arthritis & Rheumatism 49, no. 1 (February 7, 2003): 147–48. http://dx.doi.org/10.1002/art.10916.

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42

Conrozier, Thierry, Pierre Mathieu, Muriel Piperno, Huguette Favret, Frédéric Colson, Martine Vignon, Sylvie Conrozier, and Eric Vignon. "Selection of knee radiographs for trials of structure-modifying drugs in patients with knee osteoarthritis: A prospective, longitudinal study of lyon schuss knee radiographs with the definition of adequate alignment of the medial tibial plateau." Arthritis & Rheumatism 52, no. 5 (May 2005): 1411–17. http://dx.doi.org/10.1002/art.21024.

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43

Devauchelle-pensec, Valerie, Thierry Josseaume, Isabelle Samjee, Maxime Dougados, Bernard Combe, and Alain Saraux. "Ability of oblique foot radiographs to detect erosions in early arthritis: Results in the ESPOIR cohort." Arthritis & Rheumatism 59, no. 12 (December 15, 2008): 1729–34. http://dx.doi.org/10.1002/art.24310.

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44

Moran, Helen, Shun-Le Chen, Kenneth D. Muirden, Shao-Ji Jiang, Yue-Ying Gu, John Hopper, Pei-Lin Jiang, Gary Lawler, and Mark Xu Jung Bai. "A comparison of changes seen on radiographs of rheumatoid arthritis patients in australia and in china." Arthritis & Rheumatism 30, no. 11 (November 1987): 1298–302. http://dx.doi.org/10.1002/art.1780301114.

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45

Kong, S. Y., T. V. Stabler, L. G. Criscione, A. L. Elliott, J. M. Jordan, and V. B. Kraus. "Diurnal variation of serum and urine biomarkers in patients with radiographic knee osteoarthritis." Arthritis & Rheumatism 54, no. 8 (2006): 2496–504. http://dx.doi.org/10.1002/art.21977.

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46

Peat, George, Elaine Thomas, Rachel Duncan, Laurence Wood, Ross Wilkie, Jonathan Hill, Elaine M. Hay, and Peter Croft. "Estimating the probability of radiographic osteoarthritis in the older patient with knee pain." Arthritis & Rheumatism 57, no. 5 (June 15, 2007): 794–802. http://dx.doi.org/10.1002/art.22785.

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47

Heijde, Désirée van der, Robert Landewé, Xenofon Baraliakos, Harry Houben, Astrid van Tubergen, Paul Williamson, Weichun Xu, Daniel Baker, Neil Goldstein, and Jürgen Braun. "Radiographic findings following two years of infliximab therapy in patients with ankylosing spondylitis." Arthritis & Rheumatism 58, no. 10 (October 2008): 3063–70. http://dx.doi.org/10.1002/art.23901.

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48

Neame, Rebecca, Weiya Zhang, Chris Deighton, Michael Doherty, Sally Doherty, Peter Lanyon, and Gary Wright. "Distribution of radiographic osteoarthritis between the right and left hands, hips, and knees." Arthritis & Rheumatism 50, no. 5 (2004): 1487–94. http://dx.doi.org/10.1002/art.20162.

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49

Kavanaugh, Arthur. "Implications of radiographic joint damage in rheumatoid arthritis: Comment on the editorial by Weisman." Arthritis & Rheumatism 54, no. 6 (2006): 2035. http://dx.doi.org/10.1002/art.21898.

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50

Westhoff, Gisela, Rolf Rau, and Angela Zink. "Radiographic joint damage in early rheumatoid arthritis is highly dependent on body mass index." Arthritis & Rheumatism 56, no. 11 (2007): 3575–82. http://dx.doi.org/10.1002/art.23033.

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