Medical Image Retrieval Based on Shape Features in DCT Domain

Ling Xia, Zhi Peng, AnDong Cai, Haibin Wang

Abstract


Compressed medical images are widely used in clinical teaching and diagnosis. To save computing cost and storage spaces, research on compressed medical image retrieval is meaningful. This paper proposes a novel medical image retrieval scheme in DCT (Discrete Cosine Transformation) compressed domain. We firstly obtain the multi resolution image by reorganizing the DCT coefficients, then, segment the medical image’s ROI (Region of Interest) and acquires the shape binary image in DCT compressed domain. We use Hu invariant moments to extract shape feature vectors, and measure the similarity by weighting method. Experiments were carried out on an image database which contains 1000 medical CT images. The experimental results show that this algorithm can correctly extract shape features of ROI and get good retrieval performance on JPEG medical images.

 

DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.4413

 


Full Text:

PDF

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

shopify stats IJEECS visitor statistics