content-based medical image retrieval based on image feature projection in relevance feedback level

Clicks: 283
ID: 144347
2014
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #13 of 31 articles by views in annals of the university of oradea: economic science

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
The purpose of this study is to design a content-based medical image retrieval system and provide a new method to reduce semantic gap between visual features and semantic concepts. Generally performance of the retrieval systems based on only visual contents decrease because these features often fail to describe the high level semantic concepts in user’s mind. In this paper this problem is solved using a new approach based on projection of relevant and irrelevant images in to a new space with low dimensionality and less overlapping in relevance feedback level. For this purpose, first we change the feature space using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) techniques and then classify the feedback images applying Support Vector Machine (SVM) classifier. The proposed framework has been evaluated on a database consisting of 10,000 medical X-ray images of 57 semantic classes. The obtained results show that the proposed approach significantly improves the accuracy of retrieval system.
Reference Key
behnam2014journalcontent-based Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Mohammad Behnam;Hossein Pourghasem
Journal annals of the university of oradea: economic science
Year 2014
DOI
DOI not found
URL
http://jipet.iaun.ac.ir/pdf_5519_a46f1e8fe557e3031075f4b671061100.html
Keywords
principal component analysis content-based image retrieval linear discriminant analysis electronics nuclear engineering

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.