Automated reduction the speckle noise of the panoramic ultrasound images of Muscles and Tendons

Shaima Ibraheem Jabbar, Charles Day, Edward Chadwick

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)
3 Downloads (Pure)


Removing or reducing speckle noise is one of the main goals to ensure high quality panoramic ultrasound images of muscles and tendons. The presence of noise in the ultrasound image adds a difficulty in the interpretation of the image by clinicians and researchers. In this work, non-liner filter (local adaptive median filter (LAMF1)) has been developed to do a precise detection for speckle noise pixels and reduce its impact on the ultrasound images. It has been applied on three different types of ultrasound images: Based on using set of assessment metrics: Speckle Suppression Index (SSI), Speckle Suppression Mean Preservation Index (SMPI), Enhanced Edge Index (EEI) and Mean Preservation Speckle Suppression Index (MPSSI)), the new local adaptive median filter (LAMF2) has been compared to LAMF1 and Anisotropic Diffusion Filter (ADF). The performance of developed filter (LAMF2) outperformed the performance of LAMF1 as follows: SSI (3%), SMPI (4.79%), EEI (3.7%) and MPSSI (40%). Besides that, ADF has a high level of SSI, SMPI and MPSSI compared to new filter (LAMF2). However, ADF reported better numerical evaluations (EEI) than LAMF2. It is possible to obtain further performance improvements by combining characteristics of both filters (LAMF2 and ADF).

Original languageEnglish
Article number012085
Number of pages15
JournalJournal of Physics: Conference Series
Issue number1
Publication statusPublished - 17 Nov 2020
Event1st International Conference on Pure Science, ISCPS 2020 - Najaf, Virtual, Iraq
Duration: 13 Jul 202014 Jul 2020


  • Non linear filters
  • Speckle Noise Assessment Metrics and Musculoskeletal Ultrasound Imaging
  • Speckle Noise Image Enhancement


Dive into the research topics of 'Automated reduction the speckle noise of the panoramic ultrasound images of Muscles and Tendons'. Together they form a unique fingerprint.

Cite this