The week's pick
Random Articles
Reseach Article
FEMD Algorithm for Effective Segmentation of CT Lung Images
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 111 - Number 8 |
| Year of Publication: 2015 |
| Authors: Z. Faizal Khan, Syed Usama Quadri |
10.5120/19559-1311
|
Z. Faizal Khan, Syed Usama Quadri . FEMD Algorithm for Effective Segmentation of CT Lung Images. International Journal of Computer Applications. 111, 8 ( February 2015), 21-24. DOI=10.5120/19559-1311
Abstract
Medical Image segmentation is the most important step in extracting information from medical images. Segmentation of pulmonary Chest Computed Tomography (CT) images is a precursor to most of the pulmonary image analysis schemes. The purpose of lung image segmentation is to separate the voxels corresponding to lung tissue from the anatomy of the surrounding. In this paper, an automated image segmentation method has been proposed inorder to segment the region of interest present in the CT Lung slices. The proposed approach utilizes Fuzzy logic with Earth Mover's Distance (FEMD) based refinement methods. The final segmented output is further refined by morphological based operators. The performance of the proposed method is compared with various segmentation methods such as Canny Sobel and Prewitt and we have obtained an average segmentation accuracy of 79. 4091% for segmenting CT lung images.
References
- Wei Cao, Yixin Yan, Shengming Li, Unsupervised color-texture image segmentation based on a new clustering method, Journal of Next Generation Information Technology Vol. 1, Issue 2, August 2010, pp. 784–787.
- Armato S. G. and Sensakovic W. F. , Automated Lung segmentation for thoracic CT, Acad. Radiol. , Vol. 11, Issue 9, 2004, pp. 1011-1021.
- M. ArfanJaffar, Ayyaz Hussain, Anwar Majid Mirza," Fuzzy Entropy Based Optimization of Clusters for the Segmentation of Lungs in CT Scanned Images", Knowledge Information Systems, Vol. 24, pp. 91-111, 2010.
- Nuno Vieira Lopes, Pedro A. , Mogadouro do Couto, and Humberto Bustince, Automatic histogram threshold using fuzzy measures, IEEE Transactions On Image Processing, Vol. 19, Issue 1, January 2010, pp. 199-204.
- Amit Adam, Ron Kimmel and Ehud Rivlin, On scene segmentation and histograms-based curve evolution, IEEE Transactions on pattern analysis and machine intelligence, Vol. 31, Issue 9, September 2009, pp. 1708-1714
- Xujiong Ye. , Xinyu Lin, Jamshid Dehmeshki, Greg Slabaugh, and Gareth Beddoe, Shape-based computer-aided detection of Lung nodules in thoracic CT Images, IEEE Transactions on Biomedical Engineering, Vol. 56, Issue 7, July 2009, pp. 1810-1820.
- Zheng B. , Leader J. K. , Maitz G. S. , Chapman B. E. , Fuhrman C. R. , Rogers R. M. , Sciurba F. C. , Perez A. , Thompson P. , Good W. F. , and Gur D. , A simple method for automated Lung segmentation in X-ray CT images, Proc. SPIE (Medical Imaging), Vol. 5032, 2003, pp. 1455–1463.
- Faizal Khan, Z. , and Kavitha, V. , 2012, Pulmonary lung segmentation in Computer tomography using Fuzzy logic, European Journal of Scientific Research, Vol. 81, No. 3, pp. 329-337.
- Antonelli M, Lazzerini B, Marcelloni F "Segmentation and Reconstruction of the Lung Volume in CT Images". 20th annual ACM symposium on applied computing, vol I. Santa Fe, New Mexico, pp. 255-259, March 2005.
- Faizal Khan, Z & Kannan, "Intelligent Segmentation of Medical images using Fuzzy Bitplane Thresholding", "Measurement science and Review, Vol 14, No 2, pp-94-101, 2014.
- Hoffman EA, McLennan G, "Assessment of the pulmonary structure-function relationship and clinical outcomes measures Quantitative volumetric CT of the lung", AcadRadiol, Vol. 4, No. 11, pp. 758-776, 1997.
Index Terms
Keywords