THE STUDY OF MEDICAL IMAGE RETRIEVAL SYSTEM USING CBIR

Main Article Content

Fatema Aliakbar Jamnagarwala
Dr.V.K Shandilya

Abstract

Image retrieval systems attempts to search through a database to find images that are quite similar to a query image. This work aims to develop an efficient visual-Content-based technique to search, browse and retrieve relevant images from large-scale of medical image collections Features play a vital role during the image retrieval. The various features that can be extracted are texture, color, intensity, shape, resolution, global and local features etc. In this work, our focus is on the specific medical domain. The features such as color may not prove to be a very efficient method because the medical domain largely deals with the gray scale images. The features explored in this work are intensity, texture. The first step is to extract the texture feature and the intensity feature from the given input image. The resulting image is compared to the images in the database. The top most resembling images are then retrieved from the database.

Downloads

Download data is not yet available.

Article Details

Section
Articles

References

Ivica Dimitrovski, Dejan Gorgevik, Suzana Loskovska â€WebBased Medical Image Retrieval Systemâ€Faculty of Electrical Engineering and Information Technology.

R. Datta, D. Joshi, J. Li, J.Z. Wang,†Image Retrieval:

Ideas, Influences, and Trends of the New Age, ACM Transactions on Computing Surveysâ€, Vol. No 20.

Rajkumar Goel, Vineet Kumar, Saurabh Srivastava,A. K. Sinha†A Review of Feature Extraction Techniques for Image Analysis†Vol. 6, Special Issue 2, February 2017, IJARCCE.

https://en.wikipedia.org/wiki/Contentbased_image_retrieval

Y. Fanid Fathabad ,M.A. Balafar,†CONTENT BASED IMAGE RETRIEVAL FOR MEDICAL IMAGESâ€Vol.4,Issue 12,September2012,Pages177-182.

E. Acar, S. Arslan, A. Yazici, M. Koyuncu, Slim-Tree and Bit matrix Index Structures in Image Retrieval System Using MPEG-7 Descriptors, Sixth International Workshop on Content-Based Multimedia Indexing (CBMI-2008), 2008.

https://link.springer.com/chapter/10.1007/978-3-642-32112-2_16

Gurmeet Kaur and Er. Arshdeep Singh “A Review Paper on Content Based Image Retrieval†Kaur et al., International Journal of Advanced Research in Computer Science and Software Engineering 5(4), pp. 1404-1406, April- 2015,

Tobias Weyand, Thomas Deselaers, Combining Content-based Image Retrieval with Textual Information Retrieval, RWTH Aachen October 2005

http://www.enggjournals.com/ijcse/doc/IJCSE11-03-04-030.pdf

Chi-Ren Shyu, ASSERT: A Physician-in-the-loop Content-Based Retrieval System for HRCT Image Databases, Computer Vision and Image Understanding: CVIUASSERT, 1999

http://www.gnu.org/software/gift/

http://www.irmaproject

org/projekte_en.php?SELECTED=00085.

http://en.wikipedia.org/