Improving medical image perception by hierarchical clustering based segmentation

It has been well documented that radiologists' performance is not perfect: they make both false positive and false negative decisions. For example, approximately thirty percent of early lung cancer is missed on chest radiographs when the evidence is clearly visible in retrospect. Currently computer-aided detection (CAD) uses software, designed to reduce errors by drawing radiologists' attention to possible abnormalities by placing prompts on images. Alberdi et al examined the effects of CAD prompts on performance, comparing the negative effect of no prompt on a cancer case with prompts on a normal case. They showed that no prompt on a cancer case can have a detrimental effect on reader sensitivity and that the reader performs worse than if the reader was not using CAD. This became particularly apparent when difficult cases were being read. They suggested that the readers were using CAD as a decision making tool instead of a prompting aid. They conclude that "incorrect CAD can have a detrimental effect on human decisions". The goal of this paper is to explore the possibility of using hierarchical clustering based segmentation (HSC), as a perceptual aid, to improve the performance of the reader

Improving medical image perception by hierarchical clustering based segmentation

It has been well documented that radiologists' performance is not perfect: they make both false positive and false negative decisions. For example, approximately thirty percent of early lung cancer is missed on chest radiographs when the evidence is clearly visible in retrospect [1]. Currently Computer-Aided Detection (CAD) uses software, designed to reduce errors by drawing radiologists' attention to possible abnormalities by placing prompts on images. Alberdi et al examined the effects of CAD prompts on performance, comparing the negative effect of no prompt on a cancer case with prompts on a normal case. They showed that no prompt on a cancer case can have a detrimental effect on reader sensitivity and that the reader performs worse than if the reader was not using CAD. This became particularly apparent when difficult cases were being read. They suggested that the readers were using CAD as a decision making tool instead of a prompting aid. They conclude that "incorrect CAD can have a detrimental effect on human decisions" [2]. The goal of this paper is to explore the possibility of using Hierarchical Clustering based Segmentation (HCS) [3], as a perceptual aid, to improve the performance of the reader

A Review of Analog Audio Scrambling Methods for Residual Intelligibility

In this paper, a review of the techniques available in different categories of audio scrambling schemes is done with respect to Residual Intelligibility. According to Shannon's secure communication theory, for the residual intelligibility to be zero the scrambled signal must represent a white signal. Thus the scrambling scheme that has zero residual intelligibility is said to be highly secure. Many analog audio scrambling algorithms that aim to achieve lower levels of residual intelligibility are available. In this paper a review of all the existing analog audio scrambling algorithms proposed so far and their properties and limitations has been presented. The aim of this paper is to provide an insight for evaluating various analog audio scrambling schemes available up-to-date. The review shows that the algorithms have their strengths and weaknesses and there is no algorithm that satisfies all the factors to the maximum extent. Keywords: residual Intelligibility, audio scrambling, speech scramblin

Hyers-Ulam stability of a certain Fredholm integral equation

In this paper, by using Fixed point Theorem we establish the Hyers-Ulam stability and Hyers-Ulam-Rassias stability of certain homogeneous Fredholm Integral equation of the second kind and non-homogeneous equation.info:eu-repo/semantics/publishedVersio

Iron environment non-equivalence in both octahedral and tetrahedral sites in NiFe2O4 nanoparticles: study using Mössbauer spectroscopy with a high velocity resolution

Mössbauer spectrum of NiFe2O4 nanoparticles was measured at room temperature in 4096 channels. This spectrum was fitted using various models, consisting of different numbers of magnetic sextets from two to twelve. Non-equivalence of the 57Fe microenvironments due to various probabilities of different Ni2+ numbers surrounding the octahedral and tetrahedral sites was evaluated and at least 5 different microenvironments were shown for both sites. The fit of the Mössbauer spectrum of NiFe 2O4 nanoparticles using ten sextets showed some similarities in the histograms of relative areas of sextets and calculated probabilities of different Ni2+ numbers in local microenvironments. © 2012 American Institute of Physics

Enhancing the Thermal and Mechanical Properties of Organic-Inorganic Hybrid Nanocomposite Films Based on Poly Lactic Acid/OMMT Nano Clay

Abstract: Organic (PLA) inorganic (OMMT nano clay) hybrid nanocomposite films were fabricated using poly lactic acid (PLA) with various weight percentages (1-3wt%) of organically modified montmorillonite (OMMT) nano clay by means of one step solvent casting method. The thermal, mechanical and water absorption properties were determined as per standard testing methods to determine the optimum percentage of OMMT nano clay within the nanocomposite was investigated. The surface morphology of the organic-inorganic hybrid nanocomposite films was analyzed through XRD, SEM, and TEM surface analytical techniques. The incorporation of OMMT clay in to PLA matrix is found to have enhanced the thermo-mechanical properties. The water absorption and solubility test results also support the data from thermo-mechanical tests. The 2 wt % OMMT clay loaded PLA films showed the best results among all. The obtained results showed that the thermal, mechanical and water absorption properties could be increased significantly with the optimum incorporation of OMMT nano clay in a PLA matrix, in comparision wih the neat PLA

Principal Component Analysis Applied to Surface Electromyography: A Comprehensive Review

© 2016 IEEE. Surface electromyography (sEMG) records muscle activities from the surface of muscles, which offers a wealth of information concerning muscle activation patterns in both research and clinical settings. A key principle underlying sEMG analyses is the decomposition of the signal into a number of motor unit action potentials (MUAPs) that capture most of the relevant features embedded in a low-dimensional space. Toward this, the principal component analysis (PCA) has extensively been sought after, whereby the original sEMG data are translated into low-dimensional MUAP components with a reduced level of redundancy. The objective of this paper is to disseminate the role of PCA in conjunction with the quantitative sEMG analyses. Following the preliminaries on the sEMG methodology and a statement of PCA algorithm, an exhaustive collection of PCA applications related to sEMG data is in order. Alongside the technical challenges associated with the PCA-based sEMG processing, the envisaged research trend is also discussed

Low-level laser therapy for carpal tunnel syndrome

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