Authors : Ryan Kamal Said Ahemed; Zeinab Adam Mustafa; Banazier Ahmed Abrahim; Musab Elkheir Salih

Volume/Issue : Volume 10 - 2025, Issue 8 - August

Google Scholar : https://tinyurl.com/3st7nrfj

Scribd : https://tinyurl.com/39z9v8sx

DOI : https://doi.org/10.38124/ijisrt/25aug206

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Abstract : The use of DICOM for storing and transmitting medical images is essential for medical diagnosis, but this causes image degradation due to compression artifacts. Ultrasound image restoration plays a vital role in restoring image quality for precise diagnosis and treatment strategy planning. This paper presents a systematic review of three groups of DICOM compressed ultrasound image restoration techniques (contrast restoration, de blocking and deburring), focusing on methods to improve contrast, reduce blocking artifacts, and recover blurry details. The adopted techniques are already used in ordi- nary ultrasound image degradation restoration, but in this study they were modified and then applied to medical DICOM compressed ultrasound images, to test whether they are effective in compression artifact restoration or not. In this study, adaptive histogram equalization and contrast stretching was used to restore contrast loss, for blocking artifacts, Winner filtering, median filtering, bilateral filtering, and total variation filtering are evaluated for their effectiveness in preserving edge information while mitigating unwanted artifacts. Additionally, de-blurring techniques, including Blind Deconvolution, Winner filtering, and Lucy-Richardson Deconvolution, are assessed for their ability to reverse the effects of motion or defo- cus blur. The performance of these restoration methods is compared based on quantitative measures (MSE, SNR, PSNR, SSIM and QI) and qualitative results, highlighting their strengths and limitations. Our findings demonstrate that a combi- nation of these techniques can significantly improve the quality of DICOM compressed medical ultrasound images, contrib- uting to more reliable diagnostic outcomes.

Keywords : Degradations, Contrast Restoration, Total Variation Filtering, Blind Deconvolution, Lucy-Richardson Deconvolution, DICOM, Lossy JEPG Compression.

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