A Systematic Review of DICOM Compressed Medical Ultrasound Image Restoration Techniques

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.

Authors

Publication Details

Published
2025-08-14
DOI
https://doi.org/10.38124/ijisrt/25aug206
Primary Topic
Advanced Image Processing Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Systematic Review of DICOM Compressed Medical Ultrasound Image Restoration Techniques

Zeinab A. Mustafa, Musab Elkheir Salih, Banazier Ahmed Abrahim, Ryan Kamal Said Ahemed
Advanced Image Processing Techniques
article

A Systematic Review of DICOM Compressed Medical Ultrasound Image Restoration Techniques

Zeinab A. Mustafa, Musab Elkheir Salih, Banazier Ahmed Abrahim, Ryan Kamal Said Ahemed
article en

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.

Sustainable cities and communities
Openalex Percentile: Top 29%
Advanced Image Processing Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A Systematic Review of DICOM Compressed Medical Ultrasound Image Restoration Techniques — Zeinab A. Mustafa, Musab Elkheir Salih, et al. · (2025) | TGRS Research Map | TGRS