An Ultrasound Image Enhancement Method Using Neutrosophic Similarity Score

Area of Science:

• Medical Imaging
• Image Processing
• Neutrosophic Theory

Background:

• Ultrasound images often suffer from low contrast and noise, hindering accurate abnormality detection.
• Effective image enhancement is crucial for improving diagnostic accuracy in medical imaging.

Purpose of the Study:

• To propose and evaluate a novel enhancement method for ultrasound images.
• To reduce noise and improve contrast in ultrasound images using a neutrosophic approach.

Main Methods:

• The proposed method utilizes scaling with neutrosophic similarity score (NSS).
• Images are processed in the neutrosophic domain (T, I, F membership subsets).
• NSS is calculated based on intensity, local mean intensity, and edge detection to extract enhanced coefficients for image scaling.

Main Results:

• The enhancement method demonstrated significant improvements in contrast and noise reduction.
• Subjective evaluation showed a 44% increase in image quality scores compared to original images.
• Objective measures confirmed superior performance in brightness preservation, edge preservation, structural similarity, and overall image quality.

Conclusions:

• The proposed neutrosophic similarity score-based enhancement method effectively improves ultrasound image quality.
• This technique can enhance computer-aided diagnosis systems and assist radiologists in decision-making.