Review on Medical Image Retrieval Based on Wavelet, Bag of Features and Relevance Feedback

Author:

Ahmed Syed Tanzeem1,Raza Dr. Nikhat2

Affiliation:

1. Resarch Scholar, Department of CSE, M.P.U Bhopal, Madhya Pradesh, India

2. Professor, Department of CSE, M P.U Bhopal, Madhya Pradesh, India

Abstract

Technological advances have evolved in all the directions including the biomedical, because of which a record number of lives are saved every day. The advancement has now surpassed the tools level, now the doctors with the help of new tools can also detect diseases, which saves the response time. In this paper, we will work on one such technique which will help in retrieving the similar type of images with the help of their features. In this paper, the features such as Texture features, LBP features, Retrieval feature, which are processed with hash coding and relevance feedback to get the final results. The framework provides the output utilizing a hash coding classifiers which predict the image from the database of the images. The images are classified on a global level with the help of multiple low-level features.

Publisher

Technoscience Academy

Subject

General Medicine

Reference18 articles.

1. SukhadaAloni, “Content-Based Image Retrieval in Biomedical Images Using SVM Classification with Relevance Feedback”, International Journal of Scientific and Research Publications, Volume 3, Issue 11, November 2013 1 ISSN 2250-3153.

2. P. Mohanaiah, P. Sathyanarayana, L. GuruKumar, “Image Texture Feature Extraction Using GLCM Approach”, International Journal of Scientific and Research Publications, Volume 3, Issue 5, May 2013.

3. Liu Shuanga,b, Chen Deyun Chen Zhifengc and Pang Mingd, “Multi-feature fusion method for medical image retrieval using wavelet and bag-of-features”,Online Journal homepage: https://www.tandfonline.com/loi/icsu21,28 Jan 2019

4. Greg Pass, RaminZabih, “Histogram Refinement for Content-Based Image Retrieval”

5. P.Praveen Kumar D.AparnaDr. K VenkataRao, “Compact Descriptors For Accurate Image Indexing And Retrieval: Fcth And Cedd”, International Journal of Engineering Research & Technology (IJERT), Vol. 1 Issue 8, October – 2012.

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