An Ultrasound Image Enhancement Method Using Neutrosophic Similarity Score

Abstract

Ultrasound images, having low contrast and noise, adversely impact in the detection of abnormalities. In view of this, an enhancement method is proposed in this work to reduce noise and improve contrast of ultrasound images. The proposed method is based on scaling with neutrosophic similarity score (NSS), where an image is represented in the neutrosophic domain through three membership subsets T, I, and F denoting the degree of truth, indeterminacy, and falseness, respectively. The NSS measures the belonging degree of pixel to the texture using multi-criteria that is based on intensity, local mean intensity and edge detection. Then, NSS is utilized to extract the enhanced coefficient and this enhanced coefficient is applied to scale the input image. This scaling reflects contrast improvement and denoising effect on ultrasound images. The performance of proposed enhancement method is evaluated on clinical ultrasound images, using both subjective and objective image quality measures. In subjective evaluation, with proposed method, overall best score of 4.3 was obtained and that was 44% higher than the score of original images. These results were also supported by objective measures. The results demonstrated that the proposed method outperformed the other methods in terms of mean brightness preservation, edge preservation, structural similarity, and human perception-based image quality assessment. Thus, the proposed method can be used in computer-aided diagnosis systems and to visually assist radiologists in their interactive-decision-making task.

A Comparative Study on X-Ray image Enhancement Based on Neutrosophic Set

“…Nakagami distribution and applied gamma variation [13]. Bharti et al proposed a method for liver image enhancement based on the NS similarity score (NSS) [14]. An additional proposal sought to improve ultrasound images by optimizing the NLM algorithm, which is based on the weighted function [15].…”

Context-aware POI Recommendation using Neutrosophic Set for Mobile Edge Computing

“…Neutrosophic set has been widely used in image processing [22,23], pattern recognition [24] and medical diagnosis [25,26,8]. Neutrosophic set is widely used to solve MCDM problems because it can represent fuzzy decision information in multiple dimensions.…”

“…For one-dimensional attributes such as geographical location and interest topic, the neutrosophic set transformation method based on similarity calculation is adopted; for multi-dimensional attributes such as popularity and social relationship, the neutrosophic set transformation method based on sentiment analysis is adopted. The work completed in the second part (steps [19][20][21][22][23][24][25] is to obtain the POI ranking recommendation result by using the neutrosophic sets matrix corresponding to the candidate POI obtained in the previous part. In this part, the maximum deviation method is used to calculate the weight of each attribute, and the comparison algorithm of SVNN is used to compare the candidate POI.…”

A novel neutrosophic divergence score for enhancement of mammogram images

“…𝛾median filtering was used to decrease the indeterminacy and reduce noise. Bharti and Mittal (Bharti 2020) enhanced ultrasound images where the image is initially converted into neutrosophic domain and then using NSS (Neutrosophic similarity score), they enhanced the image. Shahin et.…”