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Medical Image Segmentation using Modified Morphological Reconstruction
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 86 - Number 2 |
| Year of Publication: 2014 |
| Authors: A. Nithya, R. Kayalvizhi |
10.5120/14958-3129
|
A. Nithya, R. Kayalvizhi . Medical Image Segmentation using Modified Morphological Reconstruction. International Journal of Computer Applications. 86, 2 ( January 2014), 20-26. DOI=10.5120/14958-3129
Abstract
The objective of this research is to improve the accuracy of object segmentation in medical images by constructing an object segmentation algorithm. Image segmentation is a crucial step in the field of image processing and pattern recognition. Segmentation allows the identification of structures in an image which can be utilized for further processing. Both region-based and object-based segmentation are utilized in a robust and principled manner. Gradient based MultiScalE Graylevel mOrphological recoNstructions (G-SEGON) is used for segmenting an image. SEGON roughly identifies the background and object regions in the image. The proposed method takes advantage of segmentation of both gray scale image and color image.
References
- D. Comanicu and P. Meer,"Mean shift: A robust approach toward feature space analysis", Pearson Education Ltd. , IEEE Trans. Pattern Anal. Mach. Intell. , vol. 24, no. 5, pp. 603-619, May 2002.
- Y. Deng and B. S. Manjunath,"Unsupervised segmentation of colour texture regions in images and video," IEEE Trans. Pattern Anal. Mach. Intell. , vol. 23, no. 8, pp. 800810, Aug. 2001.
- M. P. Pathegama and. Gl,"Edge-end pixel extraction for edge based image segmentation", in Proc. World Acad. Sci. Eng. Technology. , vol. 2, pp. 164-167, Jan. 2005.
- D. Sasirekha and Dr. E. Chandra, "ContourEnhanced Techniques for PDF Image Segmentation and Text Extraction," International Journal of Computer Science and Information Security, vol. 10, no. 9, pp. 7-27, 2001.
- Velthuizen. R et al. ,"Unsupervised measurement of brain tumour volume on MR images," Journal of magnetic resonance imaging, vol. 4, pp. 594-605, 1995.
- Vinitski. S et al. : Improved intracranial lesion characterization by tissue segmentation based on a 3D feature map, Journal of magnetic resonance in medicine, vol. 5, pp. 457-469, 1997.
- Gerig. G. : Automated segmentation of dual-echo MR head data, Proceedings of IPMI, pp. 175-185, 1991.
- M. C. Jobin Christ and Dr. R. M. S. Parvathi, "Magnetic resonance Brain image segmentation," International Journal of VLSI design & Communication Systems, vol. 3, no. 4, pp. 121-133, 2012.
- P. Salembier and F. Marques, "Region-based representations of image and video-segmentation tools for multimedia services, "IEEE Trans. Circuits Syst. Video Technol. , vol. 9, no. 8, pp. 1147–1169, Dec. 1999.
- Fitsum Admasua, Stephan Al-Zubia, Klaus Toenniesa, Nils Bodammerb and Hermann Hinrichsb, "Segmentation of Multiple Sclerosis Lesions from MR Brain Images Using the Principles of Fuzzy-Connectedness and Artificial Neuron Networks", In Proceedings of International Conference on Image Processing, Barcelona, Spain, Vol. 3, 2003.
- Jiann-Jone Chen, Chun-Rong Su, W. Eric L. Grimson, Jun-Lin Liu, and De-Hui Shiue,"Object Segmentation of Database Images by Dual Multiscale Morphological Reconstructions and Retrieval Applications",IEEE Transactions On Image Processing, Vol. 21, No. 2, February 2012.
- P. T. Jackway,"Morphological scale space, in Proc. 11th IAPR Int. Conf. Pattern Recognition, The Hague, The Netherlands, September 1992.
- P. Salembier and M. Pardas,"Hierarchical morphological segmentation for image sequence coding," IEEE Trans. Image Processing, vol. 3, pp. 639-651, Sept. 1994.
- P. Mirunalini, R. Nanmozhi,"Segmentation Using Multiscale Morphological Reconstruction,"SSN College of Engg, Chennai, 2013.
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