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Comparative Performance Analysis of Local Feature Descriptors for Biomedical Image Retrieval

  • Suchita Sharma
  • Ashutosh Aggarwal
Conference paper
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 30)

Abstract

Biomedical imaging field is growing enormously from last decade. The medical images have been used and stored continuously for diagnosis as well as research purposes. There exist several methods that tend to provide real-time retrieval of medical images from such storage repositories. Therefore, in this paper, we strive to present an exhaustive performance comparison of existing and recently published state-of-the-art local feature descriptors for retrieval of CT and MR images. All the compared methods have been tested on two standard test databases, namely, NEMA CT and NEMA MRI. Additional experiments have been conducted to analyze the noise robustness ability of all the compared approaches. Lastly, the methods are also compared in terms of their computational complexity and total CPU time taken to retrieve images corresponding to the given query image.

Keywords

Image retrieval Noise robustness 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringThapar Institute of Engineering and TechnologyPatialaIndia

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