We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Reseach Article

Detection of Early Stage of Osteoarthritis with the Help of Image Processing Technique

Published on September 2015 by Bhagyashri L. Wagaj, and M.m.patil
Emerging Applications of Electronics System, Signal Processing and Computing Technologies
Foundation of Computer Science USA
NCESC2015 - Number 2
September 2015
Authors: Bhagyashri L. Wagaj, and M.m.patil
fc80e944-3405-4b2b-989c-65adb991ce8a

Bhagyashri L. Wagaj, and M.m.patil . Detection of Early Stage of Osteoarthritis with the Help of Image Processing Technique. Emerging Applications of Electronics System, Signal Processing and Computing Technologies. NCESC2015, 2 (September 2015), 1-4.

@article{
author = { Bhagyashri L. Wagaj, and M.m.patil },
title = { Detection of Early Stage of Osteoarthritis with the Help of Image Processing Technique },
journal = { Emerging Applications of Electronics System, Signal Processing and Computing Technologies },
issue_date = { September 2015 },
volume = { NCESC2015 },
number = { 2 },
month = { September },
year = { 2015 },
issn = 0975-8887,
pages = { 1-4 },
numpages = 4,
url = { /proceedings/ncesc2015/number2/22365-7332/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 Emerging Applications of Electronics System, Signal Processing and Computing Technologies
%A Bhagyashri L. Wagaj
%A and M.m.patil
%T Detection of Early Stage of Osteoarthritis with the Help of Image Processing Technique
%J Emerging Applications of Electronics System, Signal Processing and Computing Technologies
%@ 0975-8887
%V NCESC2015
%N 2
%P 1-4
%D 2015
%I International Journal of Computer Applications
Abstract

Osteoarthritis (OA) is commonly seen among older people and it is arthritic type disease. It is a degenerative joint disease where cartilage slowly degenerates. Cartilage that shelters the bone ensures the smooth crusade of the joints. In knee OA, exaggerated bones come into contact due to degradation of cartilage, causing swell, discomfort and defeat of motion. Due to stress, knee joints can be frequently incapacitated and broken. The early detection of KOA could alert people to slow down the progression of the illness. Encouraged by this, the paper presents an automatic method to diagnose the Osteoarthritis disease. The cartilage of knee joint is segmented with pixel based segmentation method. For segmentation the texture filter method is applied. From segmented image cartilage area is calculated and depending on its estimated value image is classified into normal and OA affected. Osteoarthritis (OA) is commonly seen among older people and it is arthritic type disease. It is a degenerative joint disease where cartilage slowly degenerates. Cartilage that shelters the bone ensures the smooth crusade of the joints. In knee OA, exaggerated bones come into contact due to degradation of cartilage, causing swell, discomfort and defeat of motion. Due to stress, knee joints can be frequently incapacitated and broken. The early detection of KOA could alert people to slow down the progression of the illness. Encouraged by this, the paper presents an automatic method to diagnose the Osteoarthritis disease. The cartilage of knee joint is segmented with pixel based segmentation method. For segmentation the texture filter method is applied. From segmented image cartilage area is calculated and depending on its estimated value image is classified into normal and OA affected.

References
  1. Chao Jin, Yang Yang, Zu Jun Xae, Ke-Min Liu, Jing Liu , "Automated analysis method for screening knee Osteoarthritis using medical Infrared Thermography " J. Med. Biol. Eng. , Vol. 33 No. 5 2013.
  2. M. S. Mallikarjuna Swamy, Mallikarjun S. Holi,;- "Knee Joint Articular Cartilage Segmentation, Visualization and Quantification using Image Processing Techniques: A Review" International Journal of Computer Applications (0975 – 8887) Volume 42– No. 19, March 2012.
  3. Sanjeevakumar Kubakaddi, Dr KM Ravikumar," Measurement of Cartilage Thickness for Early Detection of Knee Osteoarthritis(KOA)", 2013 IEEE Point-of-Care Healthcare Technologies (PHT) Bangalore, India, 16 - 18 January, 2013.
  4. M S Mallikarjuna Swamy & Mallikarjun S Holi, "Knee Joint Articular Cartilage Segmentation using Radial Search Method, Visualization and Quantification", International Journal of Biometrics and Bioinformatics (IJBB), Volume (7): Issue (1): 2013.
  5. ] M. S. MallikarjunaSwamy and M. S. Holi, "Knee Joint Articular Cartilage Segmentation, Visualization and Quantification using Image Processing Techniques: A Review" International Journal of Computer Applications (0975 – 8887) Volume 42– No. 19, March 2012.
  6. Pierre Dodin, Jean Pierre Pelletier, Johanne Martel Pelletier and François Abram, "Automatic human knee cartilage segmentation from 3D magnetic resonance images", IEEE Trans. Biomedical Engineering, vol. 57, pp. 2699-2711, 2010.
  7. Jose G. Tamez Pena, Joshua Farber, Patricia C. Gonzalez, Edward Schreyer, Erika Schneider, and Saara Totterman, "Unsupervised segmentation and quantification of anatomical knee features: Data from the Osteoarthritis Initiative", IEEE Trans. Biomedical Engineering, vol. 59, pp. 1177-1186, 2012 .
  8. Peter M. M. Cashman, Richard I. Kitney, Munir A. Gariba, and Mary E. Carter, "Automated techniques for visualization and mapping of articular cartilage in MR images of the osteoarthritic knee: a base technique for the assessment of microdamage and submicro damage", IEEE Trans. on Nanobioscience, vol. 1, no. 1, pp. 42-51, 2002.
  9. Poh C. L. and Richard I. K. , "Viewing interfaces for segmentation and measurement results", Proc. of 27th Annual Conf. IEEE Engineering in Medicine and Biology, Shanghai, China, 2005, pp. 5132-5135.
  10. Chao Jin, Yang Yang, Zu Jun Xae, Ke-Min Liu, Jing Liu , "Automated analysis method for screening knee Osteoarthritis using medical Infrared Thermography " J. Med. Biol. Eng. , Vol. 33 No. 5 2013.
  11. Kshirsagar, M. D. Robson, P. J. Watson, N. J. Herrod, J. A. Tyler and L. D. Hall, "Computer analysis of MR images of human knee joints to measure femoral cartilage thickness", Proc. of 18th Annual Int. Conf. IEEE.
  12. Zohara A. Cohen, Denise M. Mccarthy, S. Daniel Kwak, Perrine Legrand, Fabian Fogarasi, Edward J. Ciaccio And Gerard A. Ateshian, "Knee cartilage topography, thickness, and contact areas from MRI: in-vitro calibration and in-vivo measurements", Osteoarthritis and Cartilage, vol. 7, pp. 95–109, 1999.
  13. Julio Carballido-Gamio, Jan S. Bauer1, Keh-Yang Lee, Stefanie Krause, and Sharmila Majumdar, "Combined image processing techniques for characterization of MRI cartilage of the knee", Proc. 27th Annual Conf. IEEE Engineering in Medicine and Biology, Shanghai, China, 2005 , pp. 3043-3046.
  14. Tina Kapur, Paul A. Beardsley, Sarah F. Gibson, W. Eric L. Grimson, and William M. Wells, "Model based segmentation of clinical knee MRI", Proc. of the 6th Int. Conf. on Computer Vision (ICCV-98), Bombay, India, 1998.
  15. Cristián Tejos, Laurance D. Hall, and Arturo Cárdenas-Blanco, "Segmentation of articular cartilage using active contours and prior knowledge", Proc. of the 26th Annual Int. Conf. of the IEEE EMBS, San Francisco, CA, USA , 2004, pp. 1648-1651.
  16. Jinshan Tang, Steven Millington, Scott T. Acton, Jeff Crandall, and Shepard Hurwitz, "Surface extraction and thickness measurement of the articular cartilage from MR images using directional gradient vector flow snakes", IEEE Trans. on Biomedical Engineering, vol. 53, no. 5, pp. 896-907, 2006.
  17. Hussain Z. Tameem, Luis E. Selva, and Usha S. Sinha, "Morphological atlases of knee cartilage: shape indices to analyze cartilage degradation in osteoarthritic and non-osteoarthritic population", Proc. of 29th Annual Int. Conf. of the IEEE EMBS, Cité Internationale, Lyon, France, 2007, pp. 1310-1313.
  18. Jurgen Fripp, Sebastien Ourselin, Simon K. Warfield, and Stuart Crozier, "Automatic segmentation of the bones from MR images of the knee", Proc. IEEE 4th Int. Symposium on Biomedical Imaging (ISBI-'07), Metro Washington DC, USA, 2007, pp. 336-339.
Index Terms

Computer Science
Information Sciences

Keywords

Cartilage Magnetic Resonance Imaging (mri) Osteoarthritis (oa).