Multi-panel medical image segmentation framework for image retrieval system

• Published in: Multimedia tools and applications 2018-08, Vol.77 (16), p.20271-20295
• Main Authors: Ali, Mushtaq, Dong, Le, Akhtar, Rizwan
• Format: Article
• Language: English
• Subjects: Accuracy; Borders; Color; Computer Communication Networks; Computer Science; Data Structures and Information Theory; Efficiency; Image management; Image retrieval; Image segmentation; Medical imaging; Multimedia Information Systems; Special Purpose and Application-Based Systems
• ISSN: 1380-7501; 1573-7721
• DOI: 10.1007/s11042-017-5453-8

The automatic segmentation of multi-panel medical images into sub-images improves the retrieval accuracy of medical image retrieval systems. However, the accuracy and efficiency of the available multi-panel medical image segmentation techniques are not satisfactory for multi-panel images containing homogenous color inter-panel borders and image boundary, heterogeneous color inter-panel borders, small size sub-images, or numerous number of sub-images. In order to improve the accuracy and efficiency, a Multi-panel Medical Image Segmentation Framework (MIS-Framework) is proposed and implemented based on locating the longest inter-panel border inside the boundary of the input image. We evaluated the proposed framework on a subset of imageCLEF 2013 dataset containing 2407 images. The proposed framework showed promising experimental results in terms of accuracy and efficiency on single panel as well as multi-panel image class identification and on sub-image separation as compared to the available techniques.