A Comparative Multi Method Study For Cardiac Ultrasound Image Enhancement Using Retinex Based

Arvyandita, Talitha Bertha (2026) A Comparative Multi Method Study For Cardiac Ultrasound Image Enhancement Using Retinex Based. Undergraduate thesis, UPN Veteran Jawa Timur.

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Abstract

Cardiovascular disease is the leading cause of death worldwide, making accurate diagnosis essential. Cardiac ultrasound (echocardiography) is a commonly used imaging modality, yet its images often suffer from low visual quality due to speckle noise, poor contrast, and uneven illumination. This study conducts a multi-method comparative analysis for cardiac ultrasound image enhancement using Retinex-based methods, namely Single Scale Retinex (SSR), Multi Scale Retinex (MSR), and Multi Scale Retinex with Color Restoration (MSRCR), combined with Bilateral Filter and Median Filter preprocessing, together with Contrast Limited Adaptive Histogram Equalization (CLAHE) as a non-Retinex comparison method. The cardiac ultrasound dataset was obtained from the Unity Public Portal, focusing on the parasternal long axis (PLAX) view. Six enhancement combinations (K1–K6) together with CLAHE were evaluated quantitatively using PSNR, SSIM, Entropy, and CII metrics. The results show that Retinex-based methods excel in Entropy (average 7.07) and CII (average 1.22), which are most relevant to the enhancement objective, whereas CLAHE excels in PSNR (24.32 dB) and SSIM (0.5383). Based on the aggregate score of the four metrics, stability, and the percentage of images with CII greater than 1, the K1 combination (Bilateral Filter + SSR) was determined to be the most optimal, achieving the lowest aggregate score (2.50), the highest Entropy (7.3040), and a CII > 1 percentage of 95.95%. This combination enhances contrast smoothly and evenly without introducing artifacts that interfere with clinical interpretation, making it the most suitable for cardiac ultrasound image enhancement. Keywords: cardiac ultrasound, echocardiography, image enhancement, Retinex, SSR, MSR, MSRCR, CLAHE.

Item Type:

Thesis (Undergraduate)

Contributors:

Contribution	Contributors	NIDN/NIDK	Email
Thesis advisor	Diyasa, I Gede Susrama Mas	NIDN0019067008	igsusrama.if@upnjatim.ac.id
Thesis advisor	Anggraeny, Fetty Tri	NIDN0711028201	fettyanggraeny.if@upnjatim.ac.id

Subjects:

Q Science > QA Mathematics > QA76.6 Computer Programming
Q Science > QA Mathematics > QA76.87 Neural computers

Divisions:

Faculty of Computer Science > Departemen of Informatics

Depositing User:

Talitha Bertha Arvyandita

Date Deposited:

24 Jul 2026 06:51

Last Modified:

24 Jul 2026 08:09

URI:

https://repository.upnjatim.ac.id/id/eprint/57984