Techniques for Medical Images Processing Using Shearlet Transform and Color Coding

Зотин, А. Г.; Simonov, Konstantin; Капсаргин, Ф. П.; Cherepanova, Tatyana; Kruglyakov, Alexey; Cadena, Luis

doi:10.1007/978-3-319-67994-5_9

Cited by 13 publications

(2 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The noise is basically often present in diagnostic imaging methods. Nowadays, the research has tended to focus on importance of noise reducing for example, References [ 59 , 60 , 61 ]. In connection with previous findings, reducing noise from these images is a complex task, but very important.…”

Section: Resultsmentioning

confidence: 99%

Towards to Optimal Wavelet Denoising Scheme—A Novel Spatial and Volumetric Mapping of Wavelet-Based Biomedical Data Smoothing

Stanke

Kubíček

Vilímek

et al. 2020

Sensors

View full text Add to dashboard Cite

Wavelet transformation is one of the most frequent procedures for data denoising, smoothing, decomposition, features extraction, and further related tasks. In order to perform such tasks, we need to select appropriate wavelet settings, including particular wavelet, decomposition level and other parameters, which form the wavelet transformation outputs. Selection of such parameters is a challenging area due to absence of versatile recommendation tools for suitable wavelet settings. In this paper, we propose a versatile recommendation system for prediction of suitable wavelet selection for data smoothing. The proposed system is aimed to generate spatial response matrix for selected wavelets and the decomposition levels. Such response enables the mapping of selected evaluation parameters, determining the efficacy of wavelet settings. The proposed system also enables tracking the dynamical noise influence in the context of Wavelet efficacy by using volumetric response. We provide testing on computed tomography (CT) and magnetic resonance (MR) image data and EMG signals mostly of musculoskeletal system to objectivise system usability for clinical data processing. The experimental testing is done by using evaluation parameters such is MSE (Mean Squared Error), ED (Euclidean distance) and Corr (Correlation index). We also provide the statistical analysis of the results based on Mann-Whitney test, which points out on statistically significant differences for individual Wavelets for the data corrupted with Salt and Pepper and Gaussian noise.

show abstract

Section: Resultsmentioning

confidence: 99%

Towards to Optimal Wavelet Denoising Scheme—A Novel Spatial and Volumetric Mapping of Wavelet-Based Biomedical Data Smoothing

Stanke

Kubíček

Vilímek

et al. 2020

Sensors

View full text Add to dashboard Cite

show abstract

“…The main advantage of application of neural networks in medicine is that they are capable to process a large number of parameters which are often impossible for a doctor to identify. This is the main difficulty in diagnosing because much information is the subjective assessment of doctors based on their knowledge and experience [12,13]. Nevertheless, the impact of these data on the diagnosis or choice of treatment is quite high.…”

Section: Choosing the Methods Of Treatment Of The Kidney Stone Diseasementioning

confidence: 99%

Data Modeling in the Solution of Difficult-to-Formalize Socio-Economic Problems

Симонов¹,

Kurako²,

Kabanov³

et al. 2019

J. Sib. Fed. Univ., Math. phys.

View full text Add to dashboard Cite

Algorithms for data modeling in the solution of hard-to-formalize social problems are considered in the paper. They are connected with the healthcare in terms of interconnections and interactions of territories of the Yenisei Siberia where the Krasnoyarsk Krai is the key region. Elements of information system for the analysis of the current state and estimation of the scenarios of future interaction of the territories of the Yenisei economic zone are considered to solve the problems. GIS technologies and modern approaches to model various data are described.

show abstract

Advanced Decisions in Technical and Medical Applications: An Introduction

Favorskaya

Jain

2019

Intelligent Systems Reference Library

View full text Add to dashboard Cite

Techniques for Medical Images Processing Using Shearlet Transform and Color Coding

Cited by 13 publications

References 26 publications

Towards to Optimal Wavelet Denoising Scheme—A Novel Spatial and Volumetric Mapping of Wavelet-Based Biomedical Data Smoothing

Towards to Optimal Wavelet Denoising Scheme—A Novel Spatial and Volumetric Mapping of Wavelet-Based Biomedical Data Smoothing

Data Modeling in the Solution of Difficult-to-Formalize Socio-Economic Problems

Advanced Decisions in Technical and Medical Applications: An Introduction

Contact Info

Product

Resources

About