Retrieval of head–neck medical images using Gabor filter based on power-law transformation method and rank BHMT

This research aims to work on the specific medical domain. In this work, retrieval of the head–neck medical images from a database is discussed. Content-based medical image retrieval system (CBMIR) is used for retrieving the head–neck images. CBMIR is automatic and more efficient compared with the text-based approach. Shape and texture features are used for constructing feature vector. Texture feature is extracted using a modified Gabor filter based on power-law transformation method. Shape feature is extracted using rank BHMT (rank-order blur hit or miss transformation) method. Shape and texture features are combined to form a single feature vector. Threshold value very near to zero is used to retrieve images from the database. The proposed method is compared with log-Gabor filters and rank BHMT method. Combinations of modified Gabor filter with rank BHMT gave better performance than other methods.

[1]  N. Jamil,et al.  Texture feature extraction using 2-D Gabor Filters , 2012, 2012 International Symposium on Computer Applications and Industrial Electronics (ISCAIE).

[2]  Bikesh Kumar Singh,et al.  Indexing and Retrieval of Medical Images Using CBIR Approach , 2011 .

[3]  D. P. Mital,et al.  Texture segmentation using Gabor filters , 2000, KES'2000. Fourth International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies. Proceedings (Cat. No.00TH8516).

[4]  D J Field,et al.  Relations between the statistics of natural images and the response properties of cortical cells. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[5]  Romi Satria Wahono,et al.  Color and Texture Feature Extraction Using Gabor Filter - Local Binary Patterns for Image Segmentation with Fuzzy C-Means , 2015 .

[6]  Gabriel Cristóbal,et al.  Texture Image Retrieval Based on Log-Gabor Features , 2012, CIARP.

[7]  T. S. Subashini,et al.  CLASSIFICATION OF MEDICAL X-RAY IMAGES FOR AUTOMATED ANNOTATION , 2014 .

[8]  Kamaljeet Kaur,et al.  Implementation for Gabor Filter Using on Satellite Images Enhance the Image Quality , 2013 .

[9]  R. Balasubramanian,et al.  Performance Analysis of Texture Image Retrieval in Curvelet, Contourlet, and Local Ternary Pattern Using DNN and ELM Classifiers for MRI Brain Tumor Images , 2016, CVIP.

[10]  Dan S. Bloomberg,et al.  Pattern matching using the blur hit - miss transform , 2000, J. Electronic Imaging.

[11]  M. Farajzadeh,et al.  Detection of small target based on morphological filters , 2012, 20th Iranian Conference on Electrical Engineering (ICEE2012).

[12]  K. R. Chandran,et al.  CBMIR: Content Based Medical Image Retrieval System Using Texture and Intensity for Dental Images , 2012 .

[13]  Abdul Ghafoor,et al.  Fusion of multi-focus images with registration inaccuracies , 2017, Signal Image Video Process..

[14]  Jesús Angulo,et al.  Hit-or-Miss Transform in Multivariate Images , 2010, ACIVS.

[15]  G. G. N. Gouid,et al.  Automatic identification of Head and Neck Swellings in MRI images using Support Vector Machines based on cepstral analysis , 2014 .