MyMedR

Displaying publications 1 - 20 of 53 in total

Abstract:

Sort:

Fulltext Measurements of the stiffness and thickness of the pavement asphalt layer using the enhanced resonance search method

Zakaria NM, Yusoff NI, Hardwiyono S, Nayan KA, El-Shafie A

ScientificWorldJournal, 2014;2014:594797.
PMID: 25276854 DOI: 10.1155/2014/594797

Enhanced resonance search (ERS) is a nondestructive testing method that has been created to evaluate the quality of a pavement by means of a special instrument called the pavement integrity scanner (PiScanner). This technique can be used to assess the thickness of the road pavement structure and the profile of shear wave velocity by using the principle of surface wave and body wave propagation. In this study, the ERS technique was used to determine the actual thickness of the asphaltic pavement surface layer, while the shear wave velocities obtained were used to determine its dynamic elastic modulus. A total of fifteen locations were identified and the results were then compared with the specifications of the Malaysian PWD, MDD UKM, and IKRAM. It was found that the value of the elastic modulus of materials is between 3929 MPa and 17726 MPa. A comparison of the average thickness of the samples with the design thickness of MDD UKM showed a difference of 20 to 60%. Thickness of the asphalt surface layer followed the specifications of Malaysian PWD and MDD UKM, while some of the values of stiffness obtained are higher than the standard.

Matched MeSH terms: Image Enhancement/methods*
Random walker with improved weighting function for interactive medical image segmentation

Yin LK, Rajeswari M

Biomed Mater Eng, 2014;24(6):3333-41.
PMID: 25227043 DOI: 10.3233/BME-141156

To segment an image using the random walks algorithm; users are often required to initialize the approximate locations of the objects and background in the image. Due to its segmenting model that is mainly reflected by the relationship among the neighborhood pixels and its boundary conditions, random walks algorithm has made itself sensitive to the inputs of the seeds. Instead of considering the relationship between the neighborhood pixels solely, an attempt has been made to modify the weighting function that accounts for the intensity changes between the neighborhood nodes. Local affiliation within the defined neighborhood region of the two nodes is taken into consideration by incorporating an extra penalty term into the weighting function. Besides that, to better segment images, particularly medical images with texture features, GLCM variance is incorporated into the weighting function through kernel density estimation (KDE). The probability density of each pixel belonging to the initialized seeds is estimated and integrated into the weighting function. To test the performance of the proposed weighting model, several medical images that mainly made up of 174-brain tumor images are experimented. These experiments establish that the proposed method produces better segmentation results than the original random walks.

Matched MeSH terms: Image Enhancement/methods
An efficient method for the computation of Legendre moments

Yap PT, Paramesran R

IEEE Trans Pattern Anal Mach Intell, 2005 Dec;27(12):1996-2002.
PMID: 16355666

Legendre moments are continuous moments, hence, when applied to discrete-space images, numerical approximation is involved and error occurs. This paper proposes a method to compute the exact values of the moments by mathematically integrating the Legendre polynomials over the corresponding intervals of the image pixels. Experimental results show that the values obtained match those calculated theoretically, and the image reconstructed from these moments have lower error than that of the conventional methods for the same order. Although the same set of exact Legendre moments can be obtained indirectly from the set of geometric moments, the computation time taken is much longer than the proposed method.

Matched MeSH terms: Image Enhancement/methods*
Fulltext Subspace-based technique for speckle noise reduction in ultrasound images

Yahya N, Kamel NS, Malik AS

Biomed Eng Online, 2014;13(1):154.
PMID: 25421914 DOI: 10.1186/1475-925X-13-154

Ultrasound imaging is a very essential technique in medical diagnosis due to its being safe, economical and non-invasive nature. Despite its popularity, the US images, however, are corrupted with speckle noise, which reduces US images qualities, hampering image interpretation and processing stage. Hence, there are many efforts made by researches to formulate various despeckling methods for speckle reduction in US images.

Matched MeSH terms: Image Enhancement/methods*
Benefits of 3D rotational DSA compared with 2D DSA in the evaluation of intracranial aneurysm

Wong SC, Nawawi O, Ramli N, Abd Kadir KA

Acad Radiol, 2012 Jun;19(6):701-7.
PMID: 22578227 DOI: 10.1016/j.acra.2012.02.012

The aim of this study was to compare conventional two-dimensional (2D) digital subtraction angiography (DSA) with three-dimensional (3D) rotational DSA in the investigation of intracranial aneurysm in terms of detection, size measurement, neck diameter, neck delineation, and relationship with surrounding vessels. A further aim was to compare radiation dose, contrast volume, and procedural time between the two protocols.

Matched MeSH terms: Radiographic Image Enhancement/methods
Automated pterygium detection method of anterior segment photographed images

Wan Zaki WMD, Mat Daud M, Abdani SR, Hussain A, Mutalib HA

Comput Methods Programs Biomed, 2018 Feb;154:71-78.
PMID: 29249348 DOI: 10.1016/j.cmpb.2017.10.026

BACKGROUND AND BJECTIVE: Pterygium is an ocular disease caused by fibrovascular tissue encroachment onto the corneal region. The tissue may cause vision blurring if it grows into the pupil region. In this study, we propose an automatic detection method to differentiate pterygium from non-pterygium (normal) cases on the basis of frontal eye photographed images, also known as anterior segment photographed images.
METHODS: The pterygium screening system was tested on two normal eye databases (UBIRIS and MILES) and two pterygium databases (Australia Pterygium and Brazil Pterygium). This system comprises four modules: (i) a preprocessing module to enhance the pterygium tissue using HSV-Sigmoid; (ii) a segmentation module to differentiate the corneal region and the pterygium tissue; (iii) a feature extraction module to extract corneal features using circularity ratio, Haralick's circularity, eccentricity, and solidity; and (iv) a classification module to identify the presence or absence of pterygium. System performance was evaluated using support vector machine (SVM) and artificial neural network.
RESULTS: The three-step frame differencing technique was introduced in the corneal segmentation module. The output image successfully covered the region of interest with an average accuracy of 0.9127. The performance of the proposed system using SVM provided the most promising results of 88.7%, 88.3%, and 95.6% for sensitivity, specificity, and area under the curve, respectively.
CONCLUSION: A basic platform for computer-aided pterygium screening was successfully developed using the proposed modules. The proposed system can classify pterygium and non-pterygium cases reasonably well. In our future work, a standard grading system will be developed to identify the severity of pterygium cases. This system is expected to increase the awareness of communities in rural areas on pterygium.

Matched MeSH terms: Image Enhancement/methods*
Reducing charging effects in scanning electron microscope images by Rayleigh contrast stretching method (RCS)

Wan Ismail WZ, Sim KS, Tso CP, Ting HY

Scanning, 2011 Jul-Aug;33(4):233-51.
PMID: 21611953 DOI: 10.1002/sca.20237

To reduce undesirable charging effects in scanning electron microscope images, Rayleigh contrast stretching is developed and employed. First, re-scaling is performed on the input image histograms with Rayleigh algorithm. Then, contrast stretching or contrast adjustment is implemented to improve the images while reducing the contrast charging artifacts. This technique has been compared to some existing histogram equalization (HE) extension techniques: recursive sub-image HE, contrast stretching dynamic HE, multipeak HE and recursive mean separate HE. Other post processing methods, such as wavelet approach, spatial filtering, and exponential contrast stretching, are compared as well. Overall, the proposed method produces better image compensation in reducing charging artifacts.

Matched MeSH terms: Image Enhancement/methods*
Magnetic resonance angiographic demonstration of carotid-cavernous fistula using elliptical centric time resolved imaging of contrast kinetics (EC-TRICKS)

Vattoth S, Cherian J, Pandey T

Magn Reson Imaging, 2007 Oct;25(8):1227-31.
PMID: 17442526

Magnetic resonance angiographic evaluation of the intracranial vasculature has been predominantly carried out using conventional angiographic techniques such as time of flight and phase contrast sequences. These techniques have good spatial resolution but lack temporal resolution. Newer faster angiographic techniques have been developed to circumvent this limitation. Elliptical centric time-resolved imaging of contrast kinetics (EC-TRICKS) is one such technique which has combined the use of elliptical centric ordering of the k-space with multiphase 3D digital subtraction MR angiogram (MRA) to achieve excellent temporal resolution of the arterial and venous circulations. Its applications have been mainly in the peripheral vasculature. We report the use of this technique in a case of a high-flow, direct carotid-cavernous fistula to demonstrate its potential in intracranial MR angiography.

Matched MeSH terms: Image Enhancement/methods*
Tooth mineralization stages as a diagnostic tool for assessment of skeletal maturity

Surendran S, Thomas E

Am J Orthod Dentofacial Orthop, 2014 Jan;145(1):7-14.
PMID: 24373650 DOI: 10.1016/j.ajodo.2013.09.007

The objective of this study was to determine whether dental calcification can be used as a first-level diagnostic tool for assessment of skeletal maturity.

Matched MeSH terms: Radiographic Image Enhancement/methods
Fulltext Diagnostic accuracy of digital breast tomosynthesis in combination with 2D mammography for the characterisation of mammographic abnormalities

Sanmugasiva VV, Ramli Hamid MT, Fadzli F, Rozalli FI, Yeong CH, Ab Mumin N, et al.

Sci Rep, 2020 11 26;10(1):20628.
PMID: 33244075 DOI: 10.1038/s41598-020-77456-6

This study aims to assess the diagnostic accuracy of digital breast tomosynthesis in combination with full field digital mammography (DBT + FFDM) in the charaterisation of Breast Imaging-reporting and Data System (BI-RADS) category 3, 4 and 5 lesions. Retrospective cross-sectional study of 390 patients with BI-RADS 3, 4 and 5 mammography with available histopathology examination results were recruited from in a single center of a multi-ethnic Asian population. 2 readers independently reported the FFDM and DBT images and classified lesions detected (mass, calcifications, asymmetric density and architectural distortion) based on American College of Radiology-BI-RADS lexicon. Of the 390 patients recruited, 182 malignancies were reported. Positive predictive value (PPV) of cancer was 46.7%. The PPV in BI-RADS 4a, 4b, 4c and 5 were 6.0%, 38.3%, 68.9%, and 93.1%, respectively. Among all the cancers, 76% presented as masses, 4% as calcifications and 20% as asymmetry. An additional of 4% of cancers were detected on ultrasound. The sensitivity, specificity, PPV and NPV of mass lesions detected on DBT + FFDM were 93.8%, 85.1%, 88.8% and 91.5%, respectively. The PPV for calcification is 61.6% and asymmetry is 60.7%. 81.6% of cancer detected were invasive and 13.3% were in-situ type. Our study showed that DBT is proven to be an effective tool in the diagnosis and characterization of breast lesions and supports the current body of literature that states that integrating DBT to FFDM allows good characterization of breast lesions and accurate diagnosis of cancer.

Matched MeSH terms: Radiographic Image Enhancement/methods*
Brain white and gray matter anatomy of MRI segmentation based on tissue evaluation

Salih QA, Ramli AR, Mahmud R, Wirza R

MedGenMed, 2005;7(2):1.
PMID: 16369380

Different approaches to gray and white matter measurements in magnetic resonance imaging (MRI) have been studied. For clinical use, the estimated values must be reliable and accurate when, unfortunately, many techniques fail on these criteria in an unrestricted clinical environment. A recent method for tissue clusterization in MRI analysis has the advantage of great simplicity, and it takes the account of partial volume effects. In this study, we will evaluate the intensity of MR sequences known as T1-weighted images in an axial sliced section. Intensity group clustering algorithms are proposed to achieve further diagnosis for brain MRI, which has been hardly studied. Subjective study has been suggested to evaluate the clustering group intensity in order to obtain the best diagnosis as well as better detection for the suspected cases. This technique makes use of image tissue biases of intensity value pixels to provide 2 regions of interest as techniques. Moreover, the original mathematic solution could still be used with a specific set of modern sequences. There are many advantages to generalize the solution, which give far more scope for application and greater accuracy.

Matched MeSH terms: Image Enhancement/methods*
Fulltext An automated blood vessel segmentation algorithm using histogram equalization and automatic threshold selection

Saleh MD, Eswaran C, Mueen A

J Digit Imaging, 2011 Aug;24(4):564-72.
PMID: 20524139 DOI: 10.1007/s10278-010-9302-9

This paper focuses on the detection of retinal blood vessels which play a vital role in reducing the proliferative diabetic retinopathy and for preventing the loss of visual capability. The proposed algorithm which takes advantage of the powerful preprocessing techniques such as the contrast enhancement and thresholding offers an automated segmentation procedure for retinal blood vessels. To evaluate the performance of the new algorithm, experiments are conducted on 40 images collected from DRIVE database. The results show that the proposed algorithm performs better than the other known algorithms in terms of accuracy. Furthermore, the proposed algorithm being simple and easy to implement, is best suited for fast processing applications.

Matched MeSH terms: Image Enhancement/methods*
Enhanced optical flow field of left ventricular motion using quasi-Gaussian DCT filter

Riyadi S, Mustafa MM, Hussain A, Maskon O, Nor IF

Adv Exp Med Biol, 2011;696:461-9.
PMID: 21431586 DOI: 10.1007/978-1-4419-7046-6_46

Left ventricular motion estimation is very important for diagnosing cardiac abnormality. One of the popular techniques, optical flow technique, promises useful results for motion quantification. However, optical flow technique often failed to provide smooth vector field due to the complexity of cardiac motion and the presence of speckle noise. This chapter proposed a new filtering technique, called quasi-Gaussian discrete cosine transform (QGDCT)-based filter, to enhance the optical flow field for myocardial motion estimation. Even though Gaussian filter and DCT concept have been implemented in other previous researches, this filter introduces a different approach of Gaussian filter model based on high frequency properties of cosine function. The QGDCT is a customized quasi discrete Gaussian filter in which its coefficients are derived from a selected two-dimensional DCT. This filter was implemented before and after the computation of optical flow to reduce the speckle noise and to improve the flow field smoothness, respectively. The algorithm was first validated on synthetic echocardiography image that simulates a contracting myocardium motion. Subsequently, this method was also implemented on clinical echocardiography images. To evaluate the performance of the technique, several quantitative measurements such as magnitude error, angular error, and standard error of measurement are computed and analyzed. The final motion estimation results were in good agreement with the physician manual interpretation.

Matched MeSH terms: Image Enhancement/methods
Fulltext Determination of an optimally sensitive and specific chemical exchange saturation transfer MRI quantification metric in relevant biological phantoms

Ray KJ, Larkin JR, Tee YK, Khrapitchev AA, Karunanithy G, Barber M, et al.

NMR Biomed, 2016 11;29(11):1624-1633.
PMID: 27686882 DOI: 10.1002/nbm.3614

The purpose of this study was to develop realistic phantom models of the intracellular environment of metastatic breast tumour and naïve brain, and using these models determine an analysis metric for quantification of CEST MRI data that is sensitive to only labile proton exchange rate and concentration. The ability of the optimal metric to quantify pH differences in the phantoms was also evaluated. Novel phantom models were produced, by adding perchloric acid extracts of either metastatic mouse breast carcinoma cells or healthy mouse brain to bovine serum albumin. The phantom model was validated using 1 H NMR spectroscopy, then utilized to determine the sensitivity of CEST MRI to changes in pH, labile proton concentration, T1 time and T2 time; six different CEST MRI analysis metrics (MTRasym , APT*, MTRRex , AREX and CESTR* with and without T1 /T2 compensation) were compared. The new phantom models were highly representative of the in vivo intracellular environment of both tumour and brain tissue. Of the analysis methods compared, CESTR* with T1 and T2 time compensation was optimally specific to changes in the CEST effect (i.e. minimal contamination from T1 or T2 variation). In phantoms with identical protein concentrations, pH differences between phantoms could be quantified with a mean accuracy of 0.6 pH units. We propose that CESTR* with T1 and T2 time compensation is the optimal analysis method for these phantoms. Analysis of CEST MRI data with T1 /T2 time compensated CESTR* is reproducible between phantoms, and its application in vivo may resolve the intracellular alkalosis associated with breast cancer brain metastases without the need for exogenous contrast agents.

Matched MeSH terms: Image Enhancement/methods*
Fulltext Completed local ternary pattern for rotation invariant texture classification

Rassem TH, Khoo BE

ScientificWorldJournal, 2014;2014:373254.
PMID: 24977193 DOI: 10.1155/2014/373254

Despite the fact that the two texture descriptors, the completed modeling of Local Binary Pattern (CLBP) and the Completed Local Binary Count (CLBC), have achieved a remarkable accuracy for invariant rotation texture classification, they inherit some Local Binary Pattern (LBP) drawbacks. The LBP is sensitive to noise, and different patterns of LBP may be classified into the same class that reduces its discriminating property. Although, the Local Ternary Pattern (LTP) is proposed to be more robust to noise than LBP, however, the latter's weakness may appear with the LTP as well as with LBP. In this paper, a novel completed modeling of the Local Ternary Pattern (LTP) operator is proposed to overcome both LBP drawbacks, and an associated completed Local Ternary Pattern (CLTP) scheme is developed for rotation invariant texture classification. The experimental results using four different texture databases show that the proposed CLTP achieved an impressive classification accuracy as compared to the CLBP and CLBC descriptors.

Matched MeSH terms: Image Enhancement/methods*
Profiling the features of pre-segmented healthy liver CT scans: towards fast detection of liver lesions in emergency scenario

Pasha MF, Hong KS, Rajeswari M

Annu Int Conf IEEE Eng Med Biol Soc, 2011;2011:5169-73.
PMID: 22255503 DOI: 10.1109/IEMBS.2011.6091280

Automating the detection of lesions in liver CT scans requires a high performance and robust solution. With CT-scan start to become the norm in emergency department, the need for a fast and efficient liver lesions detection method is arising. In this paper, we propose a fast and evolvable method to profile the features of pre-segmented healthy liver and use it to detect the presence of liver lesions in emergency scenario. Our preliminary experiment with the MICCAI 2007 grand challenge datasets shows promising results of a fast training time, ability to evolve the produced healthy liver profiles, and accurate detection of the liver lesions. Lastly, the future work directions are also presented.

Matched MeSH terms: Radiographic Image Enhancement/methods
Fulltext Ultrasound-guided pericardiocentesis: a novel parasternal approach

Osman A, Wan Chuan T, Ab Rahman J, Via G, Tavazzi G

Eur J Emerg Med, 2018 Oct;25(5):322-327.
PMID: 28509710 DOI: 10.1097/MEJ.0000000000000471

OBJECTIVE: The aim of this study was to evaluate a novel pericardiocentesis technique using an in-plane parasternal medial-to-lateral approach with the use of a high-frequency probe in patients with cardiac tamponade.
BACKGROUND: Echocardiography is pivotal in the diagnosis of pericardial effusion and tamponade physiology. Ultrasound guidance for pericardiocentesis is currently considered the standard of care. Several approaches have been described recently, which differ mainly on the site of puncture (subxiphoid, apical, or parasternal). Although they share the use of low-frequency probes, there is absence of complete control of needle trajectory and real-time needle visualization. An in-plane and real-time technique has only been described anecdotally.
METHODS AND RESULTS: A retrospective analysis of 11 patients (63% men, mean age: 37.7±21.2 years) presenting with cardiac tamponade admitted to the tertiary-care emergency department and treated with parasternal medial-to-lateral in-plane pericardiocentesis was carried out. The underlying causes of cardiac tamponade were different among the population. All the pericardiocentesis were successfully performed in the emergency department, without complications, relieving the hemodynamic instability. The mean time taken to perform the eight-step procedure was 309±76.4 s, with no procedure-related complications.
CONCLUSION: The parasternal medial-to-lateral in-plane pericardiocentesis is a new technique theoretically free of complications and it enables real-time monitoring of needle trajectory. For the first time, a pericardiocentesis approach with a medial-to-lateral needle trajectory and real-time, in-plane, needle visualization was performed in a tamponade patient population.

Matched MeSH terms: Image Enhancement/methods*
Determination of skin repigmentation progression

Nugroho H, Fadzil MH, Yap VV, Norashikin S, Suraiya HH

Annu Int Conf IEEE Eng Med Biol Soc, 2007;2007:3442-5.
PMID: 18002737

In this paper, we describe an image processing scheme to analyze and determine areas of skin that have undergone repigmentation in particular, during the treatment of vitiligo. In vitiligo cases, areas of skin become pale or white due to the lack of skin pigment called melanin. Vitiligo treatment causes skin repigmentation resulting in a normal skin color. However, it is difficult to determine and quantify the amount of repigmentation visually during treatment because the repigmentation progress is slow and moreover changes in skin color can only be discerned over a longer time frame typically 6 months. Here, we develop a digital image analysis scheme that can identify and determine vitiligo skin areas and repigmentation progression on a shorter time period. The technique is based on principal component analysis and independent component analysis which converts the RGB skin image into a skin image that represent skin areas due to melanin and haemoglobin only, followed by segmentation process. Vitiligo skin lesions are identified as skin areas that lack melanin (non-melanin areas). In the initial studies of 4 patients, the method has been able to quantify repigmentation in vitiligo lesion. Hence it is now possible to determine repigmentation progression objectively and treatment efficacy on a shorter time cycle.

Matched MeSH terms: Image Enhancement/methods
A comparison of wavelet and curvelet for breast cancer diagnosis in digital mammogram

Meselhy Eltoukhy M, Faye I, Belhaouari Samir B

Comput Biol Med, 2010 Apr;40(4):384-91.
PMID: 20163793 DOI: 10.1016/j.compbiomed.2010.02.002

This paper presents a comparative study between wavelet and curvelet transform for breast cancer diagnosis in digital mammogram. Using multiresolution analysis, mammogram images are decomposed into different resolution levels, which are sensitive to different frequency bands. A set of the biggest coefficients from each decomposition level is extracted. Then a supervised classifier system based on Euclidian distance is constructed. The performance of the classifier is evaluated using a 2 x 5-fold cross validation followed by a statistical analysis. The experimental results suggest that curvelet transform outperforms wavelet transform and the difference is statistically significant.

Matched MeSH terms: Image Enhancement/methods*
Fulltext Hybrid Pixel-Based Method for Cardiac Ultrasound Fusion Based on Integration of PCA and DWT

Mazaheri S, Sulaiman PS, Wirza R, Dimon MZ, Khalid F, Moosavi Tayebi R

Comput Math Methods Med, 2015;2015:486532.
PMID: 26089965 DOI: 10.1155/2015/486532

Medical image fusion is the procedure of combining several images from one or multiple imaging modalities. In spite of numerous attempts in direction of automation ventricle segmentation and tracking in echocardiography, due to low quality images with missing anatomical details or speckle noises and restricted field of view, this problem is a challenging task. This paper presents a fusion method which particularly intends to increase the segment-ability of echocardiography features such as endocardial and improving the image contrast. In addition, it tries to expand the field of view, decreasing impact of noise and artifacts and enhancing the signal to noise ratio of the echo images. The proposed algorithm weights the image information regarding an integration feature between all the overlapping images, by using a combination of principal component analysis and discrete wavelet transform. For evaluation, a comparison has been done between results of some well-known techniques and the proposed method. Also, different metrics are implemented to evaluate the performance of proposed algorithm. It has been concluded that the presented pixel-based method based on the integration of PCA and DWT has the best result for the segment-ability of cardiac ultrasound images and better performance in all metrics.

Matched MeSH terms: Image Enhancement/methods*

Filters

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links