A new method of contrast enhancement of musculoskeletal ultrasound imaging based on fuzzy inference technique

Shaima Ibraheem Jabbar*, Abathar Qahtan Aladi, Charles Day, Edward Chadwick

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Improving the clarity and visual quality of Musculoskeletal Ultrasound Images (MUI) can help clinicians to detect diseases more easily and accurately. In this work, we described how to enhance the contrast of MUI locally based on a fuzzy inference system. Local Fuzzy Inference Technique (LFIT) was introduced as a novel technique to enhance the contrast of MUI. The input data used musculoskeletal ultrasound images were collected from healthy volunteers. Local Fuzzy Inference Technique (LFIT) was compared with a recent fuzzy technique of the image enhancement and validated based on assessment metrics (second-derivative-like measure of enhancement (SDME)). The results advocated an improved quality of the musculoskeletal ultrasound images based on the LFIT technique with approximately 11% greater than recent technique and computation time of LFIT is 28.4% is less. It is possible to apply a proposal technique on the other types of image (panoramic image and video). Furthermore, observed improvements on the MUI quality could potentially invested as a pre-processing step before performing other computer vision applications, such as image segmentation, tracking, and 3D image reconstruction.

Original languageEnglish
Article number055003
Number of pages9
JournalBiomedical Physics and Engineering Express
Volume7
Issue number5
Early online date23 Jun 2021
DOIs
Publication statusPublished - 7 Jul 2021

Bibliographical note

Funding Information:
The authors would like to thank Ministry of Education of Iraq and Keele university, UK for support this work.

Keywords

  • Fuzzy inference technique
  • Image contrast assessment metrics and musculoskeletal ultrasound images
  • Image contrast enhancement

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