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Fulltext Modified algorithm for image watermarking using 2D-DCT and Elgamal Cryptosyst

Nur Azien Yazid, Kamilah Abdullah, Suhaila Abd Halim

ESTEEM Academic Journal, 2019;15(1):44-55.
MyJurnal

Image watermarking embeds identifying information in an image in such a manner that it cannot easily be removed. For the past several years, image digital watermarking has become a necessary element used for hiding secret image and enabling secured communication such as
privacy, confidentiality, authentication and data integrity. Although numerous watermarking schemes are present in grayscale images, the present work focuses on the RGB color image. This study proposed a new hybrid method that would satisfy the essential needs of modern image watermarking. The color image watermarking is based on the 2D Discrete Cosine Transform and Elgamal cryptosystem. The 2D Discrete Cosine Transform depends on the matrix products, while the Elgamal cryptosystem depends on the discrete logarithm problem. The cryptosystem is combined with existing Arnold transform in watermarking algorithm to enhance the security of secret image. Value of Peak Signal to Noise Ratio was taken as performance evaluation parameters. On the whole, the performance evaluation shows that combining the two algorithms improved the performance of image watermarking.

Matched MeSH terms: Signal-To-Noise Ratio
Modelling and optimization approach of quantitative environmental ergonomics in Malaysian Automotive Industry

Ahmad Rasdan Ismail, Baba Md Deros, Mohd Yusri Mohd Yusof, Mohd Hanifiah Mohd Haniff, Isa Halim

Journal of Occupational Safety and Health, 2012;9(1):7-13.
MyJurnal

Environmental factors such as temperature, lighting and noise have very significant impact to workers’ health, safety, comfort, performance and productivity. In an ergonomically design industrial work environment, these factors need to be control at their optimum levels. The main objective of this study is to find the effect of temperature, illuminance and sound pressure level on workers’ productivity in automotive industry. To perform this study a workstation in an automotive component manufacturing was selected as the location of the study. Results of data analysis showed there were relationships between temperature, illuminance and noise on workers’ productivity. Later, the authors’ developed multiple linear equation models to represent the relationships between temperature, illuminance and noise on the workers’ productivity. These multiple linear equation models could be used to predict the production rate for the workstation by referring to the value of temperature, illuminance and noise level.

Matched MeSH terms: Noise
Medial olivocochlear functioning and speech perception in noise in older adults

Mukari SZ, Mamat WH

Audiol. Neurootol., 2008;13(5):328-34.
PMID: 18460868 DOI: 10.1159/000128978

The purposes of this study were to: (1) compare medial olivocochlear system (MOCS) functioning and speech perception in noise in young and older adults and (2) to quantify the correlation between MOCS functioning and speech perception in noise. Measurements were taken in 20 young (mean 26.3 +/- 2.1 years) and 20 older adults (mean 55.2 +/- 2.8 years). Contralateral distortion product otoacoustic emission (DPOAE) suppression was measured to assess MOCS functioning. Speech perception in noise was evaluated using the Hearing in Noise Test in noise-ipsilateral, noise-front and noise-contralateral test conditions. The results revealed that the older group had a significantly lower high-frequency (3-8 kHz) contralateral DPOAE suppression, and performed more poorly in the noise-ipsilateral condition than the younger group. However, there was no correlation between contralateral DPOAE suppression and speech perception in noise. This study suggests that poor speech perception performance in noise experienced by older adults might be due to a decline in medial olivocochlear functioning, among other factors.

Matched MeSH terms: Noise
Measurement of subtle auditory deficit in tinnitus patients with normal audiometric thresholds using evoked otoacoustic emissions and threshold equalizing noise tests

Ishak WS, Zhao F, Rajenderkumar D, Arif M

Int Tinnitus J, 2013;18(1):35-44.
PMID: 24995898 DOI: 10.5935/0946-5448.20130006

The general consensus on the roles of hearing loss in triggering tinnitus seems not applicable in patients with normal hearing thresholds. The absence of hearing loss on the audiogram in this group of patients poses a serious challenge to the cochlear theories in explaining tinnitus generation in this group of patients.

Matched MeSH terms: Noise*
Fulltext Machine learning techniques for diabetic macular edema (DME) classification on SD-OCT images

Alsaih K, Lemaitre G, Rastgoo M, Massich J, Sidibé D, Meriaudeau F

Biomed Eng Online, 2017 Jun 07;16(1):68.
PMID: 28592309 DOI: 10.1186/s12938-017-0352-9

BACKGROUND: Spectral domain optical coherence tomography (OCT) (SD-OCT) is most widely imaging equipment used in ophthalmology to detect diabetic macular edema (DME). Indeed, it offers an accurate visualization of the morphology of the retina as well as the retina layers.
METHODS: The dataset used in this study has been acquired by the Singapore Eye Research Institute (SERI), using CIRRUS TM (Carl Zeiss Meditec, Inc., Dublin, CA, USA) SD-OCT device. The dataset consists of 32 OCT volumes (16 DME and 16 normal cases). Each volume contains 128 B-scans with resolution of 1024 px × 512 px, resulting in more than 3800 images being processed. All SD-OCT volumes are read and assessed by trained graders and identified as normal or DME cases based on evaluation of retinal thickening, hard exudates, intraretinal cystoid space formation, and subretinal fluid. Within the DME sub-set, a large number of lesions has been selected to create a rather complete and diverse DME dataset. This paper presents an automatic classification framework for SD-OCT volumes in order to identify DME versus normal volumes. In this regard, a generic pipeline including pre-processing, feature detection, feature representation, and classification was investigated. More precisely, extraction of histogram of oriented gradients and local binary pattern (LBP) features within a multiresolution approach is used as well as principal component analysis (PCA) and bag of words (BoW) representations.
RESULTS AND CONCLUSION: Besides comparing individual and combined features, different representation approaches and different classifiers are evaluated. The best results are obtained for LBP[Formula: see text] vectors while represented and classified using PCA and a linear-support vector machine (SVM), leading to a sensitivity(SE) and specificity (SP) of 87.5 and 87.5%, respectively.

Matched MeSH terms: Signal-To-Noise Ratio
Fulltext Linguistic context effects in the speech perfection of Malay-speaking normal hearing young adults

Cila Umat, Nahazatul Islia Jamari

Jurnal Sains Kesihatan Malaysia, 2006;4(1):9-20.
MyJurnal

The study examined the use of linguistic contextual cues among native, Malay-speaking normal hearing young adults. Ten undergraduate students of Universiti Kebangsaan Malaysia participated in the study. All subjects had normal hearing with the average hearing threshold levels for the overall left and the right ears of 7.8 dB (SD 4.1). The Malay Hearing in Noise Test (MyHINT) materials were employed and presented to the subjects at an approximately 65 dBA presentation level. Testing was conducted in a sound field in three different listening conditions: in quiet, in noise with +5 dB signal-to-noise ratio (SNR) and 0 dB SNR. In every test condition, three lists of MyHINT were administered to each subject. The magnitude of context effects was measured using the j factor, which was derived from measurements of recognition probabilities for whole sentences (13,) and the constituent words in the sentences (PP) in which j = log P./ log P P. Results showed that all subjects scored 100% identification of words in sentences and whole sentences in quiet listening condition, while subjects' performances in 0 dB SNR were significantly poorer than that in quiet and in +5 dB SNR (p < 0.001). The j-values were significantly correlated with the probability of recognizing words in the sentences (r = 0.515, p = 0.029) in which lower j values were associated with lower P ps. Subjects were not significantly different from each other in their use of contextual cues in adverse listening conditions [F(9, 7) = 1.34, p = 0.359]. Using the linear regression function for j on word recognition probabilities, the predicted P. were calculated. It was found that the predicted and measured probabilities of recognizing whole sentences were highly correlated: r = 0.973, p < 0.001. The results suggested that linguistic contextual information become increasingly important for recognition of sentences by normal hearing young adult listeners as SNR deteriorates.

Matched MeSH terms: Noise; Signal-To-Noise Ratio
Label-free optical spectroscopy for characterizing binding properties of highly sensitive nanocrystalline cellulose-graphene oxide based nanocomposite towards nickel ion

Daniyal WMEMM, Fen YW, Abdullah J, Sadrolhosseini AR, Saleviter S, Omar NAS

Spectrochim Acta A Mol Biomol Spectrosc, 2019 Apr 05;212:25-31.
PMID: 30594850 DOI: 10.1016/j.saa.2018.12.031

Surface plasmon resonance (SPR) is a label-free optical spectroscopy that is widely used for biomolecular interaction analysis. In this work, SPR was used to characterize the binding properties of highly sensitive nanocrystalline cellulose-graphene oxide based nanocomposite (CTA-NCC/GO) towards nickel ion. The formation of CTA-NCC/GO nanocomposite has been confirmed by FT-IR. The SPR analysis result shows that the CTA-NCC/GO has high binding affinity towards Ni2+ from 0.01 until 0.1 ppm with binding affinity constant of 1.620 × 103 M-1. The sensitivity for the CTA-NCC/GO calculated was 1.509° ppm-1. The full width at half maximum (FWHM), data accuracy (DA), and signal-to-noise ratio (SNR) have also been determined using the obtained SPR curve. For the FWHM, the value was 2.25° at 0.01 until 0.08 ppm and decreases to 2.12° at 0.1 until 10 ppm. The DA for the SPR curves is the highest at 0.01 until 0.08 ppm and lowest at 0.1 until 10 ppm. The SNR curves mirrors the curves of SPR angle shift where the SNR increases with the Ni2+ concentrations. For the selectivity test, the CTA-NCC/GO has the abilities to differentiate Ni2+ in the mixture of metal ions.

Matched MeSH terms: Signal-To-Noise Ratio
Fulltext Knowledge, attitude and practice of sawmill workers towards noise-induced hearing loss in kota bharu, kelantan

Rus RM, Daud A, Musa KI, Naing L

Malays J Med Sci, 2008 Oct;15(4):28-34.
PMID: 22589635

The purpose of this study was to determine the sawmill workers' knowledge, attitude and practice (KAP) in relation to noise-induced hearing loss (NIHL). A cross-sectional study was conducted involving 83 workers from 3 factories in Kota Bharu, Kelantan. Questionnaires were distributed to obtain the socio-demography, knowledge, attitude and practice level in relation to noise-induced hearing loss (NIHL). The weak areas identified in the knowledge section were treatment aspects (15.5%), signs and symptoms of NIHL (20.2%) and risk factors (31%). As for attitude; the prevention aspects were the lowest (25.3%), followed by risk taking attitude (26.2%), and causes of hearing loss (42.1%). Overall, the practice was not encouraging at all. It is important to have an education program to raise workers' awareness and to improve their attitude and practices towards noise-induced hearing loss.

Matched MeSH terms: Hearing Loss, Noise-Induced
Fulltext Kajian faktor-faktor fizikal terhadap tahap keselesaan bekerja di bahagian Casting Shop di kalangan pekerja di kilang pembuatan Kereta

Anuar, I., Mohamad Jauhari, J., Mohd Riduan, A.

Malaysian Journal of Community Health, 2011;17(1):42-50.
MyJurnal

Background: Level of comfort in working environment can contribute to increase level of health, emotion during working, level of safety, quality and productivity of work. A study of physical factors (heat, noise and lighting) is important to determine the level of comfort during working. This study was carried out to study those physical factors upon comfort level during working among Casting Shop workers in a car manufacturing factory.

Methods: Instruments for the physical monitoring including Questemp°36 Thermal Environment Monitor, Sound Level Meter and Lux Meter were used at seven measured areas. The information about the level of comfort during working was collected using questionnaires among 65 respondents by random sampling method.

Results: Measured data showed there were four measured areas which Wet Bulb Globe Temperature indoor (WBGTi) value are above the standard limit recommended by ACGIH, three measured areas recorded noise level above the standard limit recommended by Factories and Machineries (Noise Exposure) 1989, while there was no measured area recorded lighting reading below the standard limit recommended by MS ISO 8995:2005. Result from questionnaire found that the majority of the workers did not feel comfortable towards the heat and noise level in their workplace while most of the respondents felt comfortable towards lighting level in their workplace. Mean of WBGTi reading and lighting reading have a significant difference (p

Matched MeSH terms: Noise
Investigating the performance of an amplitude-independent algorithm for detecting the hand muscle activity of stroke survivors

Hameed HK, Wan Hasan WZ, Shafie S, Ahmad SA, Jaafar H, Inche Mat LN

J Med Eng Technol, 2020 Apr;44(3):139-148.
PMID: 32396756 DOI: 10.1080/03091902.2020.1753838

To make robotic hand devices controlled by surface electromyography (sEMG) signals feasible and practical tools for assisting patients with hand impairments, the problems that prevent these devices from being widely used have to be overcome. The most significant problem is the involuntary amplitude variation of the sEMG signals due to the movement of electrodes during forearm motion. Moreover, for patients who have had a stroke or another neurological disease, the muscle activity of the impaired hand is weak and has a low signal-to-noise ratio (SNR). Thus, muscle activity detection methods intended for controlling robotic hand devices should not depend mainly on the amplitude characteristics of the sEMG signal in the detection process, and they need to be more reliable for sEMG signals that have a low SNR. Since amplitude-independent muscle activity detection methods meet these requirements, this paper investigates the performance of such a method on people who have had a stroke in terms of the detection of weak muscle activity and resistance to false alarms caused by the involuntary amplitude variation of sEMG signals; these two parameters are very important for achieving the reliable control of robotic hand devices intended for people with disabilities. A comparison between the performance of an amplitude-independent muscle activity detection algorithm and three amplitude-dependent algorithms was conducted by using sEMG signals recorded from six hemiparesis stroke survivors and from six healthy subjects. The results showed that the amplitude-independent algorithm performed better in terms of detecting weak muscle activity and resisting false alarms.

Matched MeSH terms: Signal-To-Noise Ratio
Fulltext Investigating brain activation and neural efficacy during simple arithmetic addition task in quiet and in noise: an fMRI study

Ng, Sok Bee, Ahmad Nazlim Yusoff, Teng, Xin Ling, Aini Ismafairus Abd. Hamid

Jurnal Sains Kesihatan Malaysia, 2014;12(1):23-33.
MyJurnal

Knowledge about the hemodynamic model that mediates synaptic activity and measured magnetic resonance signal is essential in understanding brain activation. Neural efficacy is a hemodynamic parameter that would change the evoked hemodynamic responses. In this work, brain activation and neural efficacy of the activated brain areas during simple addition task in two different backgrounds were studied using fMRI. The objectives were to determine the activated areas during the performance of arithmetic addition in quiet (AIQ) and noisy (AIN) background and to investigate the relationship between neural efficacy and height extent of activation for the respective areas. Eighteen healthy male participants performed simple arithmetic addition in quiet and in noise. Bilateral cerebellum, superior temporal gyrus (STG), temporal pole (TP) and supplementary motor area (SMA) were significantly (p < 0.05) activated during AIQ and AIN. Left middle frontal gyrus (L-MFG), right superior frontal gyrus (R-SFG), right superior orbital gyrus (R-SOG) and bilateral insula were more active in quiet as compared to in noise while the left middle cingulate cortex (L-MCC), left amygdala (L-AMG), right temporal pole (R-TP) and left cerebellum (L-CER) were more active in noise as compared to in quiet. The t value for most of the activated regions was found to be inversely proportional to the neural efficacy. Significant (p < 0.05) negative relationship between t value and neural efficacy were found for R-STG and bilateral cerebellum during AIQ, while for AIN, similar relationships were found in R-CER, R-STG and R-TP. This study suggests that while being significantly activated, the hemodynamic responses of these brain regions could have been suppressed by the stimulus resulting in an intensity decrease with increasing neural efficacy.

Matched MeSH terms: Noise
Fulltext Increasing iterative reconstruction strength at low tube voltage in coronary CT angiography protocols using 3D-printed and Catphan® 500 phantoms

Abdullah KA, McEntee MF, Reed WM, Kench PL

J Appl Clin Med Phys, 2020 Sep;21(9):209-214.
PMID: 32657493 DOI: 10.1002/acm2.12977

PURPOSE: The purpose of this study was to investigate the effect of increasing iterative reconstruction (IR) algorithm strength at different tube voltages in coronary computed tomography angiography (CCTA) protocols using a three-dimensional (3D)-printed and Catphan® 500 phantoms.
METHODS: A 3D-printed cardiac insert and Catphan 500 phantoms were scanned using CCTA protocols at 120 and 100 kVp tube voltages. All CT acquisitions were reconstructed using filtered back projection (FBP) and Adaptive Statistical Iterative Reconstruction (ASIR) algorithm at 40% and 60% strengths. Image quality characteristics such as image noise, signal-noise ratio (SNR), contrast-noise ratio (CNR), high spatial resolution, and low contrast resolution were analyzed.
RESULTS: There was no significant difference (P > 0.05) between 120 and 100 kVp measures for image noise for FBP vs ASIR 60% (16.6 ± 3.8 vs 16.7 ± 4.8), SNR of ASIR 40% vs ASIR 60% (27.3 ± 5.4 vs 26.4 ± 4.8), and CNR of FBP vs ASIR 40% (31.3 ± 3.9 vs 30.1 ± 4.3), respectively. Based on the Modulation Transfer Function (MTF) analysis, there was a minimal change of image quality for each tube voltage but increases when higher strengths of ASIR were used. The best measure of low contrast detectability was observed at ASIR 60% at 120 kVp.
CONCLUSIONS: Changing the IR strength has yielded different image quality noise characteristics. In this study, the use of 100 kVp and ASIR 60% yielded comparable image quality noise characteristics to the standard CCTA protocols using 120 kVp of ASIR 40%. A combination of 3D-printed and Catphan® 500 phantoms could be used to perform CT dose optimization protocols.

Matched MeSH terms: Signal-To-Noise Ratio
Fulltext InNetGAN: Inception Network-Based Generative Adversarial Network for Denoising Low-Dose Computed Tomography

Kulathilake KASH, Abdullah NA, Bandara AMRR, Lai KW

J Healthc Eng, 2021;2021:9975762.
PMID: 34552709 DOI: 10.1155/2021/9975762

Low-dose Computed Tomography (LDCT) has gained a great deal of attention in clinical procedures due to its ability to reduce the patient's risk of exposure to the X-ray radiation. However, reducing the X-ray dose increases the quantum noise and artifacts in the acquired LDCT images. As a result, it produces visually low-quality LDCT images that adversely affect the disease diagnosing and treatment planning in clinical procedures. Deep Learning (DL) has recently become the cutting-edge technology of LDCT denoising due to its high performance and data-driven execution compared to conventional denoising approaches. Although the DL-based models perform fairly well in LDCT noise reduction, some noise components are still retained in denoised LDCT images. One reason for this noise retention is the direct transmission of feature maps through the skip connections of contraction and extraction path-based DL modes. Therefore, in this study, we propose a Generative Adversarial Network with Inception network modules (InNetGAN) as a solution for filtering the noise transmission through skip connections and preserving the texture and fine structure of LDCT images. The proposed Generator is modeled based on the U-net architecture. The skip connections in the U-net architecture are modified with three different inception network modules to filter out the noise in the feature maps passing over them. The quantitative and qualitative experimental results have shown the performance of the InNetGAN model in reducing noise and preserving the subtle structures and texture details in LDCT images compared to the other state-of-the-art denoising algorithms.

Matched MeSH terms: Signal-To-Noise Ratio
Fulltext Improving the dynamic characteristics of body-in-white structure using structural optimization

Yahaya Rashid AS, Ramli R, Mohamed Haris S, Alias A

ScientificWorldJournal, 2014;2014:190214.
PMID: 25101312 DOI: 10.1155/2014/190214

The dynamic behavior of a body-in-white (BIW) structure has significant influence on the noise, vibration, and harshness (NVH) and crashworthiness of a car. Therefore, by improving the dynamic characteristics of BIW, problems and failures associated with resonance and fatigue can be prevented. The design objectives attempt to improve the existing torsion and bending modes by using structural optimization subjected to dynamic load without compromising other factors such as mass and stiffness of the structure. The natural frequency of the design was modified by identifying and reinforcing the structure at critical locations. These crucial points are first identified by topology optimization using mass and natural frequencies as the design variables. The individual components obtained from the analysis go through a size optimization step to find their target thickness of the structure. The thickness of affected regions of the components will be modified according to the analysis. The results of both optimization steps suggest several design modifications to achieve the target vibration specifications without compromising the stiffness of the structure. A method of combining both optimization approaches is proposed to improve the design modification process.

Matched MeSH terms: Noise*
Fulltext Improved architecture of speaker recognition based on wavelet transform and Mel Frequency Cepstral Coefficient (MFCC)

Nor Ashikin Rahman, Noor Azilah Muda, Norashikin Ahmad

Pertanika Journal of Science & Technology, 2017;25(106):1-10.
MyJurnal

Combining Mel Frequency Cepstral Coefficient with wavelet transform for feature extraction is not new. This paper proposes a new architecture to help in increasing the accuracy of speaker recognition compared with conventional architecture. In conventional speaker model, the voice will undergo noise elimination first before feature extraction. The proposed architecture however, will extract the features and eliminate noise simultaneously. The MFCC is used to extract the voice features while wavelet de-noising technique is used to eliminate the noise contained in the speech signals. Thus, the new architecture achieves two outcomes in one single process: ex-tracting voice feature and elimination of noise.

Matched MeSH terms: Noise
Image signal-to-noise ratio estimation using the autoregressive model

Sim KS, Kamel NS

Scanning, 2004 7 31;26(3):135-9.
PMID: 15283250

In the last two decades, a variety of techniques for signal-to-noise ratio (SNR) estimation in scanning electron microscope (SEM) images have been proposed. However, these techniques can be divided into two groups: first, SNR estimators of good accuracy, but based on impractical assumptions; second, estimators based on realistic assumptions but of poor accuracy. In this paper we propose the implementation of autoregressive (AR)-model interpolation as a solution to the problem. Unlike others, the proposed technique is based on a single SEM image and offers the required accuracy and robustness in estimating SNR values.

Matched MeSH terms: Signal-To-Noise Ratio
Image signal-to-noise ratio estimation using Shape-Preserving Piecewise Cubic Hermite Autoregressive Moving Average model

Sim KS, Wee MY, Lim WK

Microsc Res Tech, 2008 Oct;71(10):710-20.
PMID: 18615490 DOI: 10.1002/jemt.20610

We propose to cascade the Shape-Preserving Piecewise Cubic Hermite model with the Autoregressive Moving Average (ARMA) interpolator; we call this technique the Shape-Preserving Piecewise Cubic Hermite Autoregressive Moving Average (SP2CHARMA) model. In a few test cases involving different images, this model is found to deliver an optimum solution for signal to noise ratio (SNR) estimation problems under different noise environments. The performance of the proposed estimator is compared with two existing methods: the autoregressive-based and autoregressive moving average estimators. Being more robust with noise, the SP2CHARMA estimator has efficiency that is significantly greater than those of the two methods.

Matched MeSH terms: Signal-To-Noise Ratio
Image signal-to-noise ratio and noise variance estimation using autoregressive model

Kamel NS, Sim KS

Scanning, 2004 12 23;26(6):277-81.
PMID: 15612204

During the last three decades, several techniques have been proposed for signal-to-noise ratio (SNR) and noise variance estimation in images, with different degrees of success. Recently, a novel technique based on the statistical autoregressive model (AR) was developed and proposed as a solution to SNR estimation in scanning electron microscope (SEM) image. In this paper, the efficiency of the developed technique with different imaging systems is proven and presented as an optimum solution to image noise variance and SNR estimation problems. Simulation results are carried out with images like Lena, remote sensing, and SEM. The two image parameters, SNR and noise variance, are estimated using different techniques and are compared with the AR-based estimator.

Matched MeSH terms: Signal-To-Noise Ratio
Fulltext Image quality of coronary CT angiography (CCTA) using 640-slice scanner: qualitative and quantitative assessments of coronary arteries visibility

Shahril Shamsul, Akmal Sabarudin, Hamzaini Abdul Hamid, Norzailin Abu Bakar, Oteh Maskon, Muhammad Khalis Abdul Karim

Jurnal Sains Kesihatan Malaysia, 2020;18(2):49-57.
MyJurnal

The purpose of this study was to evaluate the image quality and diagnostic accuracy of coronary computed tomography angiography (CCTA) using 640-slice scanner. Advancement of multidetector computed tomography (MDCT) technology with higher spatial, temporal resolution, and increasing detector array have improved the image quality and diagnostic accuracy of CCTA. A total of 25 patients (12 men and 13 women) underwent CCTA examination was chosen and data was acquired by 640-slice scanner. All 16 segments of coronary arteries were evaluated by two reviewers using a 4-likert scale for qualitative assessment. In quantitative assessment, the evaluation of 4 main coronary arteries were analysed in terms of signal intensity (SI), image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). All 25 patients with a mean age of 52.88 ± 14.75 years old and body mass index (BMI) of 24.24 ± 3.28 kg/m2 were analysed. In qualitative assessment, from the total of 400 segments, 379 segments (95%) had diagnostic value while 21 segments did not have diagnostic value, which means 5% artefact was detected. In quantitative assessment, there was no statistical differences in gender, race, and BMI (p>0.05). Overall evaluation showed that higher SI at the left main artery (LM) at 393.7 ± 47.19. Image noise was higher at right coronary artery (RCA) at 39.01 ± 13.97. SNR and CNR showed higher at left anterior descending (LAD) with 12.73 ± 5.17 and LM 9.14 ± 4.2, respectively. In conclusion, this study indicates that 640-slice MDCT has higher diagnostic value in CCTA examination with 95% vessel visibility with 5% artefact detection.

Matched MeSH terms: Signal-To-Noise Ratio
Image noise cross-correlation for signal-to-noise ratio estimation in scanning electron microscope images

Sim KS, Nia ME, Tso CP

Scanning, 2011 Mar-Apr;33(2):82-93.
PMID: 21381045 DOI: 10.1002/sca.20223

A new and robust parameter estimation technique, named image noise cross-correlation, is proposed to predict the signal-to-noise ratio (SNR) of scanning electron microscope images. The results of SNR and variance estimation values are tested and compared with nearest neighborhood and first-order interpolation. Overall, the proposed method is best as its estimations for the noise-free peak and SNR are most consistent and accurate to within a certain acceptable degree, compared with the others.

Matched MeSH terms: Noise; Signal-To-Noise Ratio

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