International Journal of Image, Graphics and Signal Processing(IJIGSP)
ISSN: 2074-9074 (Print), ISSN: 2074-9082 (Online)
Published By: MECS Press
IJIGSP Vol.4, No.9, Sep. 2012
Segmentation of Pre-processed Medical Images: An Approach Based on Range Filter
Full Text (PDF, 746KB), PP.8-16
Medical image segmentation is a frequent processing step. Medical images are suffering from unrelated article and strong speckle noise. In this paper, we propose an approach to remove special markings such as arrow symbols and printed text along with medical image segmentation using range filter. The special markings are extracted using Sobel edge detection technique and then the intensity values of the detected markings are substituted by the intensity values of their corresponding neighborhood pixels. Next, three different image enhancement techniques are utilized to remove strong speckle noise as well enhance the weak boundaries of medical images. Finally range filter is applied to segment the texture content of different modalities of medical image. Experiment is conducted on ImageCLEF2010 database. Results show the efficacy of our proposed approach which lead to have precise content based medical image classification and retrieval systems.
Cite This Paper
Amir Rajaei,Elham Dallalzadeh,Lalitha Rangarajan,"Segmentation of Pre-processed Medical Images: An Approach Based on Range Filter", IJIGSP, vol.4, no.9, pp.8-16, 2012.
Sinha U, Bui A, Taira R . A Review of Medical Imaging Informatics. Annals of the New York Academy of Sciences, 2002, 980(1):168-197.
Zhu J, Yang X, Du X, Song L. Pre-processing for MRI. International Journal of Computer Engineering, 2001, 27(2):25–26.
Muller H, Michoux N, Bandon D, Geissbuhler A. A Review of Content-based Medical Image Retrieval Systems in Medical Application - Clinical Benefits and Future Directions. International Journal of Medical Informatics, 2004, 73(1):1-23.
Smeulders A, Worring M, Santini S, Gupta A, Jain R. Content-Based Image Retrieval at the End of the Early Years. IEEE Transaction on Pattern Analysis and Machine Intelligence, 2000, 22(12):1380-1394.
Peng F, Yuan K, Feng S, Chen W. Pre-processing of CT Brain Images for Content-Based Image Retrieval. In: Proceedings of International Conference on BioMedical Engineering and Informatics, 2008, 208-212.
Červinka T, Provazník I. Pre-processing for Segmentation of Computer Tomography Images. In: Proceedings of RADIOELEKTRONIKA,2005, 167-170.
Hussein ZR, Rahmat RW, Nurliyana L, Saripan MI, Dimon MZ. Pre-processing Importance for Extracting Contours from Noisy Echocardiographic Images. International Journal of Computer Science and Network Security (IJCSNS),2009, 9 (3): 134-137.
Suzuki H, Toriwaki J . Automatic Segmentation of Head MRI Images by Knowledge Guided Thresholding. Journal of Computer Medical Imaging Graph, 1991, 15(4):233-240 .
Robb R A. Biomedical Imaging, Visualization and Analysis. edited by Wiley-Liss, USA, 2000 .
Williams DJ, Shah M. A Fast Algorithm for Active Contours and Curvature Estimation. CVGIP: Image Understanding, 1991, 55:14-26.
Hall Lo, Bensaid AM, Clarke LP, Velthuizen RP, Silbeger MS, Bezdek J. A Comparison of Neural Network and Fuzzy Clustering Techniques in Segmenting Magnetic Resonance Images of the Brain. IEEE Transaction on Neural Networks, 1992, 26(4): 479-486.
Cohen LD, Cohen I. Finite-element Methods for Active Contour models and Balloons for 2D and 3D Images. IEEE Transaction on Image Processing on Pattern Analysis & Machine Intelligence, 1993, 25:1131-1147.
Adalsteinsson D, Sethian JA. A Fast Level Set Method for Propagating Interfaces. Journal of Computing Physics, 1995, 118:269-277.
Li N, Liu M, Li Y . Image Segmentation Algorithm using Watershed Transform and Level Set Method. IEEE Transaction International Conference on Acoustics, Speech and Signal Processing,2007,1: 613-616.
Felzenszwalb PF, Daniel P. Efficient Graph-Based Image Segmentation. International Journal of Computer Vision, 2004, 59 (2):167-181.
Lu Y, Quan Y, Zhang Z, Wang G . MST Segmentation for Content-Based Medical Image Retrieval. In: Proceedings of International Conference on Computational Intelligent and Software Engineering, 2009, 1-4.
Cheng J, Xue R, Lu W, Jia R. Segmentation of Medical Images with Canny Operator and GVF Snake Model. In: Proceedings of 7th World Congress on Intelligent Control and Automation, 2008, 1777-1780.
Chuang C, Lie W. A Downstream Algorithm Based on Extended Gradient Vector Fellow Field for Object Segmentation. , IEEE Transaction on Image Processing, 2004, 13:1379-1392.
Wu J, Poehlman S, Nosewrthy M, Kamath MV . Texture Feature based Automated Seeded Region Growing in Abdominal MRI Segmentation. In; Proceedings of International Conference on Biomedical Engineering and Informatics, 2008,263-267.
Chang-ming Z, Guo-chang G, Hai-bo L, Jing S, Hualong Y . Segmentation of Ultrasound Image Based on Texture Feature and Graph Cut. In: Proceedings of International Conference on Computer Science and Software Engineering, 2008, 795-798.