S
Savita Gupta
Researcher at University Institute of Engineering and Technology, Panjab University
Publications - 114
Citations - 2050
Savita Gupta is an academic researcher from University Institute of Engineering and Technology, Panjab University. The author has contributed to research in topics: Image segmentation & Speckle noise. The author has an hindex of 22, co-authored 109 publications receiving 1722 citations. Previous affiliations of Savita Gupta include Panjab University, Chandigarh & Sant Longowal Institute of Engineering and Technology.
Papers
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Journal ArticleDOI
A wavelet based statistical approach for speckle reduction in medical ultrasound images
TL;DR: In this article, Chang et al. introduced a novel speckle reduction method based on soft thresholding the wavelet coefficients of the logarithmically transformed medical ultrasound image, which is based on the generalized Gaussian distributed (GGD) modeling of subband coefficients.
Proceedings Article
Image Denoising Using Wavelet Thresholding.
TL;DR: Experimental results show that the proposed threshold removes noise significantly and remains within 4% of Oracleshrink and outperforms SureShrink, BayesShRink and Wiener filtering most of the time.
Journal ArticleDOI
Full Length Article: An information fusion based method for liver classification using texture analysis of ultrasound images
TL;DR: The novelty of the proposed method is that, it combines the best features from different texture domains along with their weights and 'weighted z-score' values used to compute a discriminative index for liver classification.
Journal ArticleDOI
A Review on Ultrasound-Based Thyroid Cancer Tissue Characterization and Automated Classification:
U. R. Acharya,G. Swapna,S. V. Sree,Filippo Molinari,Savita Gupta,Rh Bardales,Agnieszka Witkowska,J. S. Suri +7 more
TL;DR: This paper discusses the different types of features that are used to study and analyze the differences between benign and malignant thyroid nodules, and presents a brief description of the commonly used classifiers in ultrasound based CAD systems.
Journal ArticleDOI
Locally adaptive wavelet domain Bayesian processor for denoising medical ultrasound images using Speckle modelling based on Rayleigh distribution
TL;DR: The main advantage of the new method over the existing techniques is that it suppresses speckle noise well, while retaining the structure of the image, particularly the thin bright streaks, which tend to occur along boundaries between tissue layers.