year 12, Issue 2 (Journal of Acoustical Engineering Society of Iran 2025)
مجله انجمن علوم صوتی ایران (مهندسی صوتیات سابق) 2025, 12(2): 17-25 |
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Mokhtari-Dizaji M, Talebian-Darzi S, ayoobi-yazdi N. Processing of consecutive ultrasound images of liver tissue with block matching algorithm to extract shear modulus of fatty liver tissue. مجله انجمن علوم صوتی ایران (مهندسی صوتیات سابق) 2025; 12 (2) : 2
URL: http://joasi.ir/article-1-301-en.html
URL: http://joasi.ir/article-1-301-en.html
Abstract: (81 Views)
The most obvious change caused by hepatic steatosis is the decreased flexibility of liver tissue. This study presents the shear displacement of liver fatty tissue from sequential B-mode ultrasound images using the block-matching algorithm. In this study, 9 men and 18 women without any underlying liver disease were examined. Ultrasound imaging was performed on individuals with both healthy and fatty livers to confirm the disease based on image brightness. The stored consecutive ultrasound images of liver tissue during stress were processed using a motion estimation algorithm to extract tissue compressibility. The shear modulus was calculated based on the relative changes in length under compressive stress. Differentiation between the two groups was performed using an independent t-test with a significance level of 0.95. The results showed a considerable increase in the mean shear modulus of fatty liver (5.41 ± 0.86 kPa) compared to healthy liver (2.30 ± 0.68 kPa) (P < 0.05). Algorithm validation was conducted through manual measurement. The results indicate that the use of the block-matching algorithm to extract the elastic properties of liver tissue can effectively distinguish between healthy liver and hepatic steatosis while minimizing user intervention.
Article number: 2
Keywords: Ultrasound waves, Image processing, Displacement estimation, Block matching algorithm, Shear modulus, Fatty liver
Type of Study: Applicable |
Subject:
Physical Acoustics
Received: 2024/09/14 | Accepted: 2024/12/14 | Published: 2025/03/18
Received: 2024/09/14 | Accepted: 2024/12/14 | Published: 2025/03/18
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