Research Article
Adaptive Content-Based Medical Image Retrieval Based On Local Features Extraction In Shearlet Domain
@ARTICLE{10.4108/eai.18-3-2019.159351, author={Vo Thi Hong Tuyet and Nguyen Mong Hien and Pham Bao Quoc and Nguyen Thanh Son and Nguyen Thanh Binh}, title={Adaptive Content-Based Medical Image Retrieval Based On Local Features Extraction In Shearlet Domain}, journal={EAI Endorsed Transactions on Context-aware Systems and Applications}, volume={6}, number={17}, publisher={EAI}, journal_a={CASA}, year={2019}, month={6}, keywords={medical image, content-based medical retrieval, segmentation, active contour model, shearlet}, doi={10.4108/eai.18-3-2019.159351} }- Vo Thi Hong Tuyet
Nguyen Mong Hien
Pham Bao Quoc
Nguyen Thanh Son
Nguyen Thanh Binh
Year: 2019
Adaptive Content-Based Medical Image Retrieval Based On Local Features Extraction In Shearlet Domain
CASA
EAI
DOI: 10.4108/eai.18-3-2019.159351
Abstract
Image retrieval system is an urgent issue for in medicine. In the past, traditional image retrieval system based solely on the label of images and gave limited results. To reduce this disadvantage, the content-based medical image retrieval has been developed. However, this system still has many challenges. In this paper, we proposed a new method for content-based medical image retrieval. The proposed method includes two stages: the offline task and online task in medical image database. In the first stage, we extracted local object features of medical images in shearlet domain. Then, we detect the contour of object in images by active contour model. In the second stage, we make online task for content-based image retrieval in database. Our system receipts a query image and shows the similar in images by similarity comparison with the information collected from the first stage. Experimental results have shown that the proposed method is better than the other methods.
Copyright © 2019 Vo Thi Hong Tuyet et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
