Displaying publications 21 - 40 of 754 in total

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  1. Siar CH, Toh CG, Ali TB, Seiz D, Ong ST
    Clin Oral Implants Res, 2012 Apr;23(4):438-46.
    PMID: 21435011 DOI: 10.1111/j.1600-0501.2010.02145.x
    A stable oral mucosa is crucial for long-term survival and biofunctionality of implants. Most of this evidence is derived from clinical and animal studies based solely on implant-supported prosthesis. Much less is known about the dimensions and relationships of this soft tissue complex investing tooth-implant-supported bridgework (TISB). The aim here was to obtain experimental evidence on the dimensional characteristics of oral mucosa around TISB with two different abutment designs.
    Matched MeSH terms: Software
  2. Nazri A, Lio P
    PLoS One, 2012;7(1):e28713.
    PMID: 22253694 DOI: 10.1371/journal.pone.0028713
    The output of state-of-the-art reverse-engineering methods for biological networks is often based on the fitting of a mathematical model to the data. Typically, different datasets do not give single consistent network predictions but rather an ensemble of inconsistent networks inferred under the same reverse-engineering method that are only consistent with the specific experimentally measured data. Here, we focus on an alternative approach for combining the information contained within such an ensemble of inconsistent gene networks called meta-analysis, to make more accurate predictions and to estimate the reliability of these predictions. We review two existing meta-analysis approaches; the Fisher transformation combined coefficient test (FTCCT) and Fisher's inverse combined probability test (FICPT); and compare their performance with five well-known methods, ARACNe, Context Likelihood or Relatedness network (CLR), Maximum Relevance Minimum Redundancy (MRNET), Relevance Network (RN) and Bayesian Network (BN). We conducted in-depth numerical ensemble simulations and demonstrated for biological expression data that the meta-analysis approaches consistently outperformed the best gene regulatory network inference (GRNI) methods in the literature. Furthermore, the meta-analysis approaches have a low computational complexity. We conclude that the meta-analysis approaches are a powerful tool for integrating different datasets to give more accurate and reliable predictions for biological networks.
    Matched MeSH terms: Software
  3. Saedi TA, Moeini H, Tan WS, Yusoff K, Daud HM, Chu KB, et al.
    Mol Biol Rep, 2012 May;39(5):5785-90.
    PMID: 22223294 DOI: 10.1007/s11033-011-1389-7
    White tail disease (WTD) is a serious viral disease in the hatcheries and nursery ponds of Macrobrachium rosenbergii in many parts of the world. A new disease similar to WTD was observed in larvae and post larvae of M. rosenbergii cultured in Malaysia. In the present study, RT-PCR assay was used to detect the causative agents of WTD, M. rosenbergii nodavirus (MrNV) and extra small virus (XSV) using specific primers for MrNV RNA2 and XSV. The results showed the presence of MrNV in the samples with or without signs of WTD. However, XSV was only detected in some of the MrNV-positive samples. Phylogenetic analysis showed that the RNA2 of our Malaysian isolates were significantly different from the other isolates. Histopathological studies revealed myofiber degeneration of the tail muscles and liquefactive myopathy in the infected prawns. This was the first report on the occurrence of MrNV in the Malaysian freshwater prawn.
    Matched MeSH terms: Software
  4. Ebin LE, Zam NM, Othman SA
    Aust Orthod J, 2010 Nov;26(2):165-70.
    PMID: 21175027
    To investigate the craniofacial morphology of Malay children with repaired UCLP and compare the data with non-cleft Malay children.
    Matched MeSH terms: Software
  5. Mohajeri S, Aziz HA, Isa MH, Zahed MA, Bashir MJ, Adlan MN
    Water Sci Technol, 2010;61(5):1257-66.
    PMID: 20220248 DOI: 10.2166/wst.2010.018
    In the present study, Electrochemical Oxidation was used to remove COD and color from semi-aerobic landfill leachate collected from Pulau Burung Landfill Site (PBLS), Penang, Malaysia. Experiments were conducted in a batch laboratory-scale system in the presence of NaCl as electrolyte and aluminum electrodes. Central composite design (CCD) under Response surface methodology (RSM) was applied to optimize the electrochemical oxidation process conditions using chemical oxygen demand (COD) and color removals as responses, and the electrolyte concentrations, current density and reaction time as control factors. Analysis of variance (ANOVA) showed good coefficient of determination (R(2)) values of >0.98, thus ensuring satisfactory fitting of the second-order regression model with the experimental data. In un-optimized condition, maximum removals for COD (48.77%) and color (58.21%) were achieved at current density 80 mA/cm(2), electrolyte concentration 3,000 mg/L and reaction time 240 min. While after optimization at current density 75 mA/cm(2), electrolyte concentration 2,000 mg/L and reaction time 218 min a maximum of 49.33 and 59.24% removals were observed for COD and color respectively.
    Matched MeSH terms: Software
  6. Mohajeri L, Aziz HA, Isa MH, Zahed MA
    Bioresour Technol, 2010 Feb;101(3):893-900.
    PMID: 19773160 DOI: 10.1016/j.biortech.2009.09.013
    This work studied the bioremediation of weathered crude oil (WCO) in coastal sediment samples using central composite face centered design (CCFD) under response surface methodology (RSM). Initial oil concentration, biomass, nitrogen and phosphorus concentrations were used as independent variables (factors) and oil removal as dependent variable (response) in a 60 days trial. A statistically significant model for WCO removal was obtained. The coefficient of determination (R(2)=0.9732) and probability value (P<0.0001) demonstrated significance for the regression model. Numerical optimization based on desirability function were carried out for initial oil concentration of 2, 16 and 30 g per kg sediment and 83.13, 78.06 and 69.92 per cent removal were observed respectively, compare to 77.13, 74.17 and 69.87 per cent removal for un-optimized results.
    Matched MeSH terms: Software
  7. Jamal N, Ng KH, Looi LM, McLean D, Zulfiqar A, Tan SP, et al.
    Phys Med Biol, 2006 Nov 21;51(22):5843-57.
    PMID: 17068368
    We describe a semi-automated technique for the quantitative assessment of breast density from digitized mammograms in comparison with patterns suggested by Tabar. It was developed using the MATLAB-based graphical user interface applications. It is based on an interactive thresholding method, after a short automated method that shows the fibroglandular tissue area, breast area and breast density each time new thresholds are placed on the image. The breast density is taken as a percentage of the fibroglandular tissue to the breast tissue areas. It was tested in four different ways, namely by examining: (i) correlation of the quantitative assessment results with subjective classification, (ii) classification performance using the quantitative assessment technique, (iii) interobserver agreement and (iv) intraobserver agreement. The results of the quantitative assessment correlated well (r2 = 0.92) with the subjective Tabar patterns classified by the radiologist (correctly classified 83% of digitized mammograms). The average kappa coefficient for the agreement between the readers was 0.63. This indicated moderate agreement between the three observers in classifying breast density using the quantitative assessment technique. The kappa coefficient of 0.75 for intraobserver agreement reflected good agreement between two sets of readings. The technique may be useful as a supplement to the radiologist's assessment in classifying mammograms into Tabar's pattern associated with breast cancer risk.
    Matched MeSH terms: Software
  8. Rahmat S, O'Beirne GA
    Hear Res, 2015 Dec;330(Pt A):125-33.
    PMID: 26209881 DOI: 10.1016/j.heares.2015.07.013
    Schroeder-phase masking complexes have been used in many psychophysical experiments to examine the phase curvature of cochlear filtering at characteristic frequencies, and other aspects of cochlear nonlinearity. In a normal nonlinear cochlea, changing the "scalar factor" of the Schroeder-phase masker from -1 through 0 to +1 results in a marked difference in the measured masked thresholds, whereas this difference is reduced in ears with damaged outer hair cells. Despite the valuable information it may give, one disadvantage of the Schroeder-phase masking procedure is the length of the test - using the conventional three-alternative forced-choice technique to measure a masking function takes around 45 min for one combination of probe frequency and intensity. As an alternative, we have developed a fast method of recording these functions which uses a Békésy tracking procedure. Testing at 500 Hz in normal hearing participants, we demonstrate that our fast method: i) shows good agreement with the conventional method; ii) shows high test-retest reliability; and iii) shortens the testing time to 8 min.
    Matched MeSH terms: Software
  9. Siddiqui MF, Reza AW, Kanesan J
    PLoS One, 2015;10(8):e0135875.
    PMID: 26280918 DOI: 10.1371/journal.pone.0135875
    A wide interest has been observed in the medical health care applications that interpret neuroimaging scans by machine learning systems. This research proposes an intelligent, automatic, accurate, and robust classification technique to classify the human brain magnetic resonance image (MRI) as normal or abnormal, to cater down the human error during identifying the diseases in brain MRIs. In this study, fast discrete wavelet transform (DWT), principal component analysis (PCA), and least squares support vector machine (LS-SVM) are used as basic components. Firstly, fast DWT is employed to extract the salient features of brain MRI, followed by PCA, which reduces the dimensions of the features. These reduced feature vectors also shrink the memory storage consumption by 99.5%. At last, an advanced classification technique based on LS-SVM is applied to brain MR image classification using reduced features. For improving the efficiency, LS-SVM is used with non-linear radial basis function (RBF) kernel. The proposed algorithm intelligently determines the optimized values of the hyper-parameters of the RBF kernel and also applied k-fold stratified cross validation to enhance the generalization of the system. The method was tested by 340 patients' benchmark datasets of T1-weighted and T2-weighted scans. From the analysis of experimental results and performance comparisons, it is observed that the proposed medical decision support system outperformed all other modern classifiers and achieves 100% accuracy rate (specificity/sensitivity 100%/100%). Furthermore, in terms of computation time, the proposed technique is significantly faster than the recent well-known methods, and it improves the efficiency by 71%, 3%, and 4% on feature extraction stage, feature reduction stage, and classification stage, respectively. These results indicate that the proposed well-trained machine learning system has the potential to make accurate predictions about brain abnormalities from the individual subjects, therefore, it can be used as a significant tool in clinical practice.
    Matched MeSH terms: Software
  10. Tisa F, Davoody M, Abdul Raman AA, Daud WM
    PLoS One, 2015;10(4):e0119933.
    PMID: 25849556 DOI: 10.1371/journal.pone.0119933
    The efficiency of phenol degradation via Fenton reaction using mixture of heterogeneous goethite catalyst with homogeneous ferrous ion was analyzed as a function of three independent variables, initial concentration of phenol (60 to 100 mg /L), weight ratio of initial concentration of phenol to that of H2O2 (1: 6 to 1: 14) and, weight ratio of initial concentration of goethite catalyst to that of H2O2 (1: 0.3 to 1: 0.7). More than 90 % of phenol removal and more than 40% of TOC removal were achieved within 60 minutes of reaction. Two separate models were developed using artificial neural networks to predict degradation percentage by a combination of Fe3+ and Fe2+ catalyst. Five operational parameters were employed as inputs while phenol degradation and TOC removal were considered as outputs of the developed models. Satisfactory agreement was observed between testing data and the predicted values (R2Phenol = 0.9214 and R2TOC= 0.9082).
    Matched MeSH terms: Software
  11. Alomari YM, Sheikh Abdullah SN, MdZin RR, Omar K
    Comput Math Methods Med, 2015;2015:673658.
    PMID: 25793010 DOI: 10.1155/2015/673658
    Analysis of whole-slide tissue for digital pathology images has been clinically approved to provide a second opinion to pathologists. Localization of focus points from Ki-67-stained histopathology whole-slide tissue microscopic images is considered the first step in the process of proliferation rate estimation. Pathologists use eye pooling or eagle-view techniques to localize the highly stained cell-concentrated regions from the whole slide under microscope, which is called focus-point regions. This procedure leads to a high variety of interpersonal observations and time consuming, tedious work and causes inaccurate findings. The localization of focus-point regions can be addressed as a clustering problem. This paper aims to automate the localization of focus-point regions from whole-slide images using the random patch probabilistic density method. Unlike other clustering methods, random patch probabilistic density method can adaptively localize focus-point regions without predetermining the number of clusters. The proposed method was compared with the k-means and fuzzy c-means clustering methods. Our proposed method achieves a good performance, when the results were evaluated by three expert pathologists. The proposed method achieves an average false-positive rate of 0.84% for the focus-point region localization error. Moreover, regarding RPPD used to localize tissue from whole-slide images, 228 whole-slide images have been tested; 97.3% localization accuracy was achieved.
    Matched MeSH terms: Software
  12. Ismail R, Rahman AF, Chand P
    J Clin Pharm Ther, 1994 Aug;19(4):245-8.
    PMID: 7989403
    We estimated individual and population Michaelis-Menten pharmacokinetic parameters for phenytoin (DPH) in epileptic patients attending our neurology clinic using the computer programme. OPT. Our results agreed well with literature values but were lower than those we obtained earlier in a smaller number of patients. The Km was independent of age, weight and sex but there was a weak, correlation between Vm and body weight. We conclude that the use of population Vm and Km in normograms could lead to errors in DPH dose estimations as they correlated very poorly with patient characteristics. OPT was easy to use and sufficiently accurate for deriving dose estimates in routine patients. Its use would enable practitioners to generate their patients' own parameters for use in individual dosage adjustments. The estimates can subsequently be updated as more data become available.
    Matched MeSH terms: Software
  13. Rosenthal VD, Bat-Erdene I, Gupta D, Belkebir S, Rajhans P, Zand F, et al.
    Infect Control Hosp Epidemiol, 2020 05;41(5):553-563.
    PMID: 32183925 DOI: 10.1017/ice.2020.20
    BACKGROUND: Short-term peripheral venous catheter-related bloodstream infection (PVCR-BSI) rates have not been systematically studied in resource-limited countries, and data on their incidence by number of device days are not available.

    METHODS: Prospective, surveillance study on PVCR-BSI conducted from September 1, 2013, to May 31, 2019, in 727 intensive care units (ICUs), by members of the International Nosocomial Infection Control Consortium (INICC), from 268 hospitals in 141 cities of 42 countries of Africa, the Americas, Eastern Mediterranean, Europe, South East Asia, and Western Pacific regions. For this research, we applied definition and criteria of the CDC NHSN, methodology of the INICC, and software named INICC Surveillance Online System.

    RESULTS: We followed 149,609 ICU patients for 731,135 bed days and 743,508 short-term peripheral venous catheter (PVC) days. We identified 1,789 PVCR-BSIs for an overall rate of 2.41 per 1,000 PVC days. Mortality in patients with PVC but without PVCR-BSI was 6.67%, and mortality was 18% in patients with PVC and PVCR-BSI. The length of stay of patients with PVC but without PVCR-BSI was 4.83 days, and the length of stay was 9.85 days in patients with PVC and PVCR-BSI. Among these infections, the microorganism profile showed 58% gram-negative bacteria: Escherichia coli (16%), Klebsiella spp (11%), Pseudomonas aeruginosa (6%), Enterobacter spp (4%), and others (20%) including Serratia marcescens. Staphylococcus aureus were the predominant gram-positive bacteria (12%).

    CONCLUSIONS: PVCR-BSI rates in INICC ICUs were much higher than rates published from industrialized countries. Infection prevention programs must be implemented to reduce the incidence of PVCR-BSIs in resource-limited countries.

    Matched MeSH terms: Software
  14. Yang HK, Ji J, Han SU, Terashima M, Li G, Kim HH, et al.
    Lancet Gastroenterol Hepatol, 2021 02;6(2):120-127.
    PMID: 33253659 DOI: 10.1016/S2468-1253(20)30315-0
    BACKGROUND: Peritoneal recurrence of gastric cancer after curative surgical resection is common and portends a poor prognosis. Early studies suggest that extensive intraoperative peritoneal lavage (EIPL) might reduce the risk of peritoneal recurrence and improve survival. We aimed to evaluate the survival benefit of EIPL in patients with gastric cancer undergoing curative gastrectomy.

    METHODS: In this open-label, phase 3, multicentre randomised trial, patients aged 21-80 years with cT3 or cT4 gastric cancer undergoing curative resection were enrolled at 22 centres from South Korea, China, Japan, Malaysia, Hong Kong, and Singapore. Patients were randomly assigned to receive surgery and EIPL (EIPL group) or surgery alone (standard surgery group) via a web-based programme in random permuted blocks in varying block sizes of four and six, assuming equal allocation between treatment groups. Randomisation was stratified according to study site and the sequence was generated using a computer program and concealed until the interventions were assigned. After surgery in the EIPL group, peritoneal lavage was done with 1 L of warm (42°C) normal 0·9% saline followed by complete aspiration; this procedure was repeated ten times. The primary endpoint was overall survival. All analyses were done assuming intention to treat. This trial is registered with ClinicalTrials.gov, NCT02140034.

    FINDINGS: Between Sept 16, 2012, and Aug 3, 2018, 800 patients were randomly assigned to the EIPL group (n=398) or the standard surgery group (n=402). Two patients in the EIPL group and one in the standard surgery group withdrew from the trial immediately after randomisation and were excluded from the intention-to-treat analysis. At the third interim analysis on Aug 28, 2019, the predictive probability of overall survival being significantly higher in the EIPL group was less than 0·5%; therefore, the trial was terminated on the basis of futility. With a median follow-up of 2·4 years (IQR 1·5-3·0), the two groups were similar in terms of overall survival (hazard ratio 1·09 [95% CI 0·78-1·52; p=0·62). 3-year overall survival was 77·0% (95% CI 71·4-81·6) for the EIPL group and 76·7% (71·0-81·5) for the standard surgery group. 60 adverse events were reported in the EIPL group and 41 were reported in the standard surgery group. The most common adverse events included anastomotic leak (ten [3%] of 346 patients in the EIPL group vs six [2%] of 362 patients in the standard surgery group), bleeding (six [2%] vs six [2%]), intra-abdominal abscess (four [1%] vs five [1%]), superficial wound infection (seven [2%] vs one [<1%]), and abnormal liver function (six [2%] vs one [<1%]). Ten of the reported adverse events (eight in the EIPL group and two in the standard surgery group) resulted in death.

    INTERPRETATION: EIPL and surgery did not have a survival benefit compared with surgery alone and is not recommended for patients undergoing curative gastrectomy for gastric cancer.

    FUNDING: National Medical Research Council, Singapore.

    Matched MeSH terms: Software
  15. Mustapha MA, Shahpudin SN, Aziz AA, Ankathil R
    World J Gastroenterol, 2012 Jun 7;18(21):2668-73.
    PMID: 22690076 DOI: 10.3748/wjg.v18.i21.2668
    To investigate the allele and genotype frequencies and associated risk of interleukin (IL)-8 -251T>A polymorphism on colorectal cancer (CRC) susceptibility risk.
    Matched MeSH terms: Software
  16. Zainul Abidin FN, Westhead DR
    Nucleic Acids Res, 2017 04 20;45(7):e53.
    PMID: 27994031 DOI: 10.1093/nar/gkw1270
    Clustering is used widely in 'omics' studies and is often tackled with standard methods, e.g. hierarchical clustering. However, the increasing need for integration of multiple data sets leads to a requirement for clustering methods applicable to mixed data types, where the straightforward application of standard methods is not necessarily the best approach. A particularly common problem involves clustering entities characterized by a mixture of binary data (e.g. presence/absence of mutations, binding, motifs and epigenetic marks) and continuous data (e.g. gene expression, protein abundance, metabolite levels). Here, we present a generic method based on a probabilistic model for clustering this type of data, and illustrate its application to genetic regulation and the clustering of cancer samples. We show that the resulting clusters lead to useful hypotheses: in the case of genetic regulation these concern regulation of groups of genes by specific sets of transcription factors and in the case of cancer samples combinations of gene mutations are related to patterns of gene expression. The clusters have potential mechanistic significance and in the latter case are significantly linked to survival. The method is available as a stand-alone software package (GNU General Public Licence) from http://github.com/BioToolsLeeds/FlexiCoClusteringPackage.git.
    Matched MeSH terms: Software
  17. Khalit WNAW, Tay KS
    Ecotoxicol Environ Saf, 2017 Nov;145:214-220.
    PMID: 28738204 DOI: 10.1016/j.ecoenv.2017.07.020
    Unmetabolized pharmaceuticals often enter the water treatment plants and exposed to various treatment processes. Among these water treatment processes, disinfection is a process which involves the application of chemical oxidation to remove pathogen. Untreated pharmaceuticals from primary and secondary treatment have the potential to be exposed to the chemical oxidation process during disinfection. This study investigated the kinetics and mechanism of the degradation of sotalol during chlorination process. Chlorination with hypochlorous acid (HOCl) as main reactive oxidant has been known as one of the most commonly used disinfection methods. The second order rate constant for the reaction between sotalol and free available chlorine (FAC) was found to decrease from 60.1 to 39.1M-1min-1 when the pH was increased from 6 to 8. This result was mainly attributed by the decreased of HOCl concentration with increasing pH. In the real water samples, the presence of the higher amount of organic content was found to reduce the efficiency of chlorination in the removal of sotalol. This result showed that sotalol competes with natural organic matter to react with HOCl during chlorination. After 24h of FAC exposure, sotalol was found to produce three stable transformation by-products. These by-products are mainly chlorinated compounds. According to the acute and chronic toxicity calculated using ECOSAR computer program, the transformation by-products are more harmful than sotalol.
    Matched MeSH terms: Software
  18. Kwong HC, Chidan Kumar CS, Mah SH, Chia TS, Quah CK, Loh ZH, et al.
    PLoS One, 2017;12(2):e0170117.
    PMID: 28241010 DOI: 10.1371/journal.pone.0170117
    Biphenyl-based compounds are clinically important for the treatments of hypertension and inflammatory, while many more are under development for pharmaceutical uses. In the present study, a series of 2-([1,1'-biphenyl]-4-yl)-2-oxoethyl benzoates, 2(a-q), and 2-([1,1'-biphenyl]-4-yl)-2-oxoethyl pyridinecarboxylate, 2(r-s) were synthesized by reacting 1-([1,1'-biphenyl]-4-yl)-2-bromoethan-1-one with various carboxylic acids using potassium carbonate in dimethylformamide at ambient temperature. Single-crystal X-ray diffraction studies revealed a more closely packed crystal structure can be produced by introduction of biphenyl moiety. Five of the compounds among the reported series exhibited significant anti-tyrosinase activities, in which 2p, 2r and 2s displayed good inhibitions which are comparable to standard inhibitor kojic acid at concentrations of 100 and 250 μg/mL. The inhibitory effects of these active compounds were further confirmed by computational molecular docking studies and the results revealed the primary binding site is active-site entrance instead of inner copper binding site which acted as the secondary binding site.
    Matched MeSH terms: Software
  19. Shanmugapriya, Huda HA, Vijayarathna S, Oon CE, Chen Y, Kanwar JR, et al.
    Adv Exp Med Biol, 2018 9 28;1087:95-105.
    PMID: 30259360 DOI: 10.1007/978-981-13-1426-1_8
    Circular RNAs characterize a class of widespread and diverse endogenous RNAs which are non-coding RNAs that are made by back-splicing events and have covalently closed loops with no polyadenylated tails. Various indications specify that circular RNAs (circRNAs) are plentiful in the human transcriptome. However, their participation in biological processes remains mostly undescribed. To date thousands of circRNAs have been revealed in organisms ranging from Drosophila melanogaster to Homo sapiens. Functional studies specify that these transcripts control expression of protein-coding linear transcripts and thus encompass a key component of gene expression regulation. This chapter provide a comprehensive overview on functional validation of circRNAs. Furthermore, we discuss the recent modern methodologies for the functional validation of circRNAs such as RNA interference (RNAi) gene silencing assay, luciferase reporter assays, circRNA gain-of-function investigation via overexpression of circular transcript assay, RT-q-PCR quantification, and other latest applicable assays. The methods described in this chapter are demonstrated on the cellular model.
    Matched MeSH terms: Software
  20. Acharya UR, Raghavendra U, Koh JEW, Meiburger KM, Ciaccio EJ, Hagiwara Y, et al.
    Comput Methods Programs Biomed, 2018 Nov;166:91-98.
    PMID: 30415722 DOI: 10.1016/j.cmpb.2018.10.006
    BACKGROUND AND OBJECTIVE: Liver fibrosis is a type of chronic liver injury that is characterized by an excessive deposition of extracellular matrix protein. Early detection of liver fibrosis may prevent further growth toward liver cirrhosis and hepatocellular carcinoma. In the past, the only method to assess liver fibrosis was through biopsy, but this examination is invasive, expensive, prone to sampling errors, and may cause complications such as bleeding. Ultrasound-based elastography is a promising tool to measure tissue elasticity in real time; however, this technology requires an upgrade of the ultrasound system and software. In this study, a novel computer-aided diagnosis tool is proposed to automatically detect and classify the various stages of liver fibrosis based upon conventional B-mode ultrasound images.

    METHODS: The proposed method uses a 2D contourlet transform and a set of texture features that are efficiently extracted from the transformed image. Then, the combination of a kernel discriminant analysis (KDA)-based feature reduction technique and analysis of variance (ANOVA)-based feature ranking technique was used, and the images were then classified into various stages of liver fibrosis.

    RESULTS: Our 2D contourlet transform and texture feature analysis approach achieved a 91.46% accuracy using only four features input to the probabilistic neural network classifier, to classify the five stages of liver fibrosis. It also achieved a 92.16% sensitivity and 88.92% specificity for the same model. The evaluation was done on a database of 762 ultrasound images belonging to five different stages of liver fibrosis.

    CONCLUSIONS: The findings suggest that the proposed method can be useful to automatically detect and classify liver fibrosis, which would greatly assist clinicians in making an accurate diagnosis.

    Matched MeSH terms: Software
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