Speckle noise reduction in ultrasound images using fuzzy logic based on histogram and directional differences

Keerthivasan, A.; Babu, J. Jai Jaganath; Sudha, Gnanou Florence

doi:10.1109/iccsp.2013.6577104

Cited by 9 publications

(3 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This problem is mostly solved by using, fuzzy sets. [25][26][27] However, the fuzzy set can only handle the membership degree and fails to deal with non-membership and indeterminacy degree of pixels. Zhuang et al enhanced ultrasound images by using fuzzy-based technique and then used these enhanced images for image segmentation.…”

Section: Introductionmentioning

confidence: 99%

An Ultrasound Image Enhancement Method Using Neutrosophic Similarity Score

Bharti

Mittal

2020

Ultrason Imaging

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionmentioning

confidence: 99%

An Ultrasound Image Enhancement Method Using Neutrosophic Similarity Score

Bharti

Mittal

2020

Ultrason Imaging

View full text Add to dashboard Cite

show abstract

“…It deteriorates the image quality and makes the differentiation of fine details difficult. The major purpose of speckle reduction is to improve the image quality [19,15] for accurate segmentation of nodules. However, the removal of speckle noise is always a trade-off between edge preservation and noise suppression.…”

Section: Introductionmentioning

confidence: 99%

Computer aided thyroid nodule detection system using medical ultrasound images

Koundal

Gupta

Singh

2018

Biomedical Signal Processing and Control

124

View full text Add to dashboard Cite

Thyroid nodule is one of the endocrine problem caused due to abnormal growth of cells. This survival rate can be enhanced by earlier detection of nodules. Thus, the accurate detection of nodule is of utmost importance in providing effective diagnosis to increase the survival rate. However, accuracy of nodule detection from ultrasound images is suffered due to speckle noise. It considerably deteriorates the image quality and makes the differentiation of fine details quite difficult. Most of the detection systems for the thyroid nodules are semi-automated entailing manual intervention to draw rough outline of the nodule at some level or require manual segmentation in training or testing phases that increase the inaccuracies and evaluation time. To handle this, a fully Computer-Aided Detection system is presented for speckle reduction and segmentation of nodules from thyroid ultrasound images. The proposed system has three components: speckle reduction to reduce speckle noise and preserve the diagnostic features of ultrasound image, automatic generation of Region of interest (ROI) that identifies suspicious regions and fully automatic segmentation of nodule in processed ROI image. The proposed segmentation method outperformed other methods by gaining high True Positive (TP) value (95.92 ± 3.70%), False Positive (FP) value (7.04 ± 4.21%), Dice Coefficient (DC) value (93.88 ± 2.59%), Overlap Metric (OM) (91.18 ± 7.04 pixels) and Hausdroff Distance (HD) (0.52 ± 0.20 pixels). This system can facilitate the endocrinologists by providing second opinion to improve diagnosis of nodules as benign or malignant.

show abstract

“…To address this issue, fuzzy domain is most widely used by the researchers to handle the fuzziness of images [8]. However, fuzzy set can handle only the membership degree but fails to deal with non-membership and indeterminacy degree of pixels.…”

Section: Introductionmentioning

confidence: 99%

Neutrosophic Based Nakagami Total Variation Method for Speckle Suppression in Thyroid Ultrasound Images

Koundal

Gupta

Singh

2018

IRBM

View full text Add to dashboard Cite

Highlights• The Neutrosophic based Nakagami based Total Variation (NTV) method has been proposed. • It can make balance between speckle reduction and edge preservation. • It is able to handle the indeterminate pixels and preserve the valuable information such as texture and edges. • It can assist endocrinologists in improving the quality of ultrasound images for accurate segmentation of thyroid nodules. Graphical abstract AbstractBackground: Neutrosophic based methods are becoming very popular in denoising of images due to the capability of handling indeterminacy. The main goal of denoising is to maintain balance between edge preservation and speckle reduction. Methods: To achieve this, neutrosophic based total variation method using Nakagami statistics have been explored to develop an efficient speckle reduction method. The proposed Neutrosophic based Nakagami Total Variation (NNTV) method initially transforms the image into the neutrosophic domain and then employs the neutrosophic filtering process for speckle reduction. The NNTV quantifies the indeterminacy of image by determining the entropy of indeterminate set.Results: The performance of the proposed method has been evaluated quantitatively by quality metrics on synthetic images, qualitatively using real thyroid ultrasound images through visual examination by medical experts and by Mean Opinion Score. Conclusion: From results, it has been observed that NNTV method performed better than other speckle reduction methods in terms of both speckle suppression and edge preservation.

show abstract

Speckle noise reduction in ultrasound images using fuzzy logic based on histogram and directional differences

Cited by 9 publications

References 18 publications

An Ultrasound Image Enhancement Method Using Neutrosophic Similarity Score

An Ultrasound Image Enhancement Method Using Neutrosophic Similarity Score

Computer aided thyroid nodule detection system using medical ultrasound images

Neutrosophic Based Nakagami Total Variation Method for Speckle Suppression in Thyroid Ultrasound Images

Contact Info

Product

Resources

About