CFP last date
15 April 2024
Call for Paper
May Edition
IJAIS solicits high quality original research papers for the upcoming May edition of the journal. The last date of research paper submission is 15 April 2024

Submit your paper
Know more
Reseach Article

Content based Medical Image Retrieval with SVM Classification and Relevance Feedback

Published on July 2013 by Sujata T Bhairnallykar, V. B. Gaikwad
International Conference and workshop on Advanced Computing 2013
Foundation of Computer Science USA
ICWAC - Number 4
July 2013
Authors: Sujata T Bhairnallykar, V. B. Gaikwad
114b2fc2-fc26-4a77-806d-5e1d64a60d1d

Sujata T Bhairnallykar, V. B. Gaikwad . Content based Medical Image Retrieval with SVM Classification and Relevance Feedback. International Conference and workshop on Advanced Computing 2013. ICWAC, 4 (July 2013), 0-0.

@article{
author = { Sujata T Bhairnallykar, V. B. Gaikwad },
title = { Content based Medical Image Retrieval with SVM Classification and Relevance Feedback },
journal = { International Conference and workshop on Advanced Computing 2013 },
issue_date = { July 2013 },
volume = { ICWAC },
number = { 4 },
month = { July },
year = { 2013 },
issn = 2249-0868,
pages = { 0-0 },
numpages = 1,
url = { /proceedings/icwac/number4/502-1318/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference and workshop on Advanced Computing 2013
%A Sujata T Bhairnallykar
%A V. B. Gaikwad
%T Content based Medical Image Retrieval with SVM Classification and Relevance Feedback
%J International Conference and workshop on Advanced Computing 2013
%@ 2249-0868
%V ICWAC
%N 4
%P 0-0
%D 2013
%I International Journal of Applied Information Systems
Abstract

As the network and development of multimedia technologies are becoming more popular, users are not satisfied with the traditional information retrieval techniques. So now a day the content based image retrieval using relevance feedback are becoming a source of exact and fast retrieval. The idea of Content-based Image Retrieval (CBIR) using Relevance Feedback systems is to automatically extract image contents based on image features, i. e. color, texture, and shape and store in database and compare input query image feature with the features stored in database. Relevance feedback is applied to reduce the gap between high-level image semantics and low-level image features. Semantic gap is the difference between human perception of a concept and how it can be represented using machine level language.

References
  1. T. C. Wong, Medical Image Databases. New York, LLC: Springer–Verlag, 1998.
  2. H. Muller, N. Michoux, D. Bandon, and Geissbuhler, "A review of content-basedimage retrieval applications—Clinical benefits and future directions," Int. J. Med. Informat. , vol. 73, no. 1, pp. 1–23, 2004.
  3. A. Smeulder, M. Worring, S. Santini, A. Gupta, and R. Jain, "Contentbased image retrieval at the end of the early years," IEEE Trans. Pattern Anal. Machine Intell vol. 22, no. 12, pp. 1349–1380, Dec. 2000.
  4. C. R. Shyu, C. E. Brodley, A. C. Kak, A. Kosaka, A. M Aisen, and L. S. Broderick, "ASSERT: A physician-in-the-loop content-based image retrieval system for HRCT image databases," Comput. Vis. Image Understand. , vol. 75, pp. 111–132, 1999.
  5. W. Hsu, S. Antani, L. R. Long, L. Neve, and G. R. Thoma, "SPIRS: A web-based image retrieval system for large biomedical databases," Int. J. Med. Informat. , vol. 78, pp. 13–24, 2008.
  6. Efficient Relevance Feedback for Content-Based Image Retrieval by Mining User Navigation Patterns -IEEE transactions on knowledge and data engineering, vol. 23, no. 3, march 2011.
  7. Balasubramani R, Dr. V. Kannan "Efficient use of MPEG-7 Color Layout and Edge Histogram Descriptors in CBIR Systems" Global Journal of Computer Science and Technology.
  8. Minyoung Eom, and Yoonsik Choe "Fast Extraction of Edge Histogram in DCT Domain based on MPEG7" World Academy of Science, Engineering and Technology 9 2005
  9. Mahesh Pal "Multiclass Approaches for Support Vector Machine Based Land Cover Classification "Lecturer, Department of Civil engineering National Institute of Technology Kurukshetra, 136119, Haryana (INDIA) mpce_pal@yahoo. co. uk
  10. M. M. Rahman, S. K. Antani, and G. R. Thoma, "A classification-driven similarity matching framework for retrieval of biomedical images," presented at the 11th ACM Int. Conf. Multimedia Inf. Retrieval, National Constitution Center, Philadelphia, Pennsylvania, Mar. 29–31.
  11. A Learning-Based Similarity Fusion and Filtering Approach for Biomedical Image Retrieval Using SVM Classification and Relevance Feedback - IEEE transactions on information technology in biomedicine, vol. 15, no. 4, july 2011.
  12. F Long, H Zhang, DD Feng "Fundamentals of Content-based Image retrieval - Multimedia Information Retrieval and Management 17, 2003- Springer
  13. Pushpa B. PATIL, Manesh B. KOKARE "Relevance Feedback in Content Based Image Retrieval: A Review" Journal of Applied Computer Science & Mathematics, no. 10 (5) /2011, Suceava
  14. Content-Based Image Retrieval: State-of-the-Art and Challenges" Amandeep Khokher et al. / (IJAEST) International Journal of Advanced Engineering Sciences and Technologies Vol No. 9, Issue No. 2, 207 - 211
Index Terms

Computer Science
Information Sciences

Keywords

Content-based image retrieval Relevance feedback SVM CLD EHD