Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
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Quantization of Lumbar Muscle using FCM Algorithm

FCM 알고리즘을 이용한 요부 근육 양자화

  • 김광백 (신라대학교 컴퓨터공학과)
  • Received : 2013.05.22
  • Accepted : 2013.08.02
  • Published : 2013.08.30
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Abstract

In this paper, we propose a new quantization method using fuzzy C-means clustering(FCM) for lumbar ultrasound image recognition. Unlike usual histogram based quantization, our method first classifies regions into 10 clusters and sorts them by the central value of each cluster. Those clusters are represented with different colors. This method is efficient to handle lumbar ultrasound image since in this part of human body, the brightness values are distributed to doubly skewed histogram in general thus the usual histogram based quantization is not strong to extract different areas. Experiment conducted with 15 real lumbar images verified the efficacy of proposed method.

본 논문에서는 요부 초음파 영상에서 퍼지 C-Means 클러스터링을 이용한 양자화 기법을 제안한다. 제안된 방법은 초음파 영상에서 나타난 명암도를 이용하여 n개의 그룹으로 클러스터링한다. 그리고 각클러스터의 중심 값을 기준으로 정렬한 뒤, 각 그룹에 지정된 색상을 요부 초음파 영상에 나타낸다. 본 논문에서 제안하는 기법과 히스토그램 기반 양자화 기법에 대해 15장의 요부 초음파 영상에 적용한 결과, 본 논문에서 제안된 양자화 방법이 효과적인 것을 확인할 수 있었다.

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References

  1. S. L. Koppenhaver, J. J. Hebert, J. M. Fritz, E. C. Parent, D. S. Teyhen, J. S. Magel JS, "Reliability of rehabilitative ultrasound imaging of the transverses abdominis and lumbar multifidus muscles," Arch Phys Med Rehabil, pp.87-94, Vol.90, No.1 Jan., 2009. https://doi.org/10.1016/j.apmr.2008.06.022
  2. K. B. Kim, S. H. Shin, "Extraction of Lumbar Multifidus Muscle using Ultrasound Images," Journal of Korea Institute of Intelligent Systems, Vol.16, No.2, pp.55-59, Feb., 2011.
  3. K. B. Kim, "Extraction of Muscle Areas form Ultrasonographic Images using Thoracic Vertebra and Subcutaneous Fat Areas," Journal of Korea Institute of Intelligent Systems, Vol.17, No.5, pp.29-32, May., 2011. https://doi.org/10.9708/jksci.2012.17.5.029
  4. M. T. V. Holsbeeck, J. H. Introcaso, "'Musculoskeletal Ultrasound", 2nd edn, Philadelphia, Mosby Press, 2001
  5. R. K. Chhem,, P. A. Kaplan, and R. G. Dussault ,"Ultrasonography of the musculoskeletal system," Radiol. Clin.. North Am.. Vol.32, pp.275-289, 1994.
  6. F. M. R. Jesus, P. H. Ferreira, M. L. Ferreira, "'Ultrasonographic Measurement of Neck Muscle Recruitment: A Preliminary Investigation", Journal Manual & Manipulative Therapy, Vol.16, pp.89-92, 2009.
  7. K. B. Kim, "Extraction of Muscle Areas form Ultrasonographic Images using Subcutaneous Fat Areas and Thoracic Vertebra," Journal of The Korea Society of Computer and Information, Vol.17, No.5, pp.29-32, 2012. https://doi.org/10.9708/jksci.2012.17.5.029
  8. J. C. Bezdek, Pattern Recognition with Fuzzy Objective Function Algorithms, Springer, 1981.
  9. D. Q. Zhanga, S. C. Chen, "A novel kernelized fuzzy C-means algorithm with application in medical image segmentation," Artificial Intelligence in Medicine, Vol. 32, Issue 1, pp.37-50, 2004. https://doi.org/10.1016/j.artmed.2004.01.012