Preprocessing Analysis on Medical Image Retrieval Using One-to-one Matching of SURF Keypoints

Ery Permana Yudha, Nanik Suciati, Chastine Fatichah

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

The development of medical image technology is increasing very rapidly. Moreover, medical image growth is predicted to grow exponentially over the past decade. Much research on medical images has been done, one of which is medical image retrieval using colors, textures, and keypoints matching. Generally, the keypoints matching approach is more reliable against spatial rotation. However, the medical images mostly contain blur objects and noise, which affect the performance of keypoints detection. This study proposes a preprocessing analysis on medical image retrieval using one-one matching of SURF keypoints. The image retrieval performance with and without preprocessing is compared on the IRMA 2009 dataset. This analysis proves that the use of preprocessing can improve the precision by 17.78%, 17.59%, and 17.92% on top-5, top-10, and top-15, respectively.

Original languageEnglish
Title of host publicationProceeding - 5th International Conference on Informatics and Computational Sciences, ICICos 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages160-164
Number of pages5
ISBN (Electronic)9781665438070
DOIs
Publication statusPublished - 2021
Event5th International Conference on Informatics and Computational Sciences, ICICos 2021 - Semarang, Indonesia
Duration: 24 Nov 202125 Nov 2021

Publication series

NameProceedings - International Conference on Informatics and Computational Sciences
Volume2021-November
ISSN (Print)2767-7087

Conference

Conference5th International Conference on Informatics and Computational Sciences, ICICos 2021
Country/TerritoryIndonesia
CitySemarang
Period24/11/2125/11/21

Keywords

  • detection
  • grayscale
  • keypoints
  • matching
  • preprocessing
  • retrieval

Fingerprint

Dive into the research topics of 'Preprocessing Analysis on Medical Image Retrieval Using One-to-one Matching of SURF Keypoints'. Together they form a unique fingerprint.

Cite this