Displaying publications 41 - 55 of 55 in total

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  1. Badsha S, Reza AW, Tan KG, Dimyati K
    J Digit Imaging, 2013 Dec;26(6):1107-15.
    PMID: 23515843 DOI: 10.1007/s10278-013-9585-8
    Diabetic retinopathy (DR) is increasing progressively pushing the demand of automatic extraction and classification of severity of diseases. Blood vessel extraction from the fundus image is a vital and challenging task. Therefore, this paper presents a new, computationally simple, and automatic method to extract the retinal blood vessel. The proposed method comprises several basic image processing techniques, namely edge enhancement by standard template, noise removal, thresholding, morphological operation, and object classification. The proposed method has been tested on a set of retinal images. The retinal images were collected from the DRIVE database and we have employed robust performance analysis to evaluate the accuracy. The results obtained from this study reveal that the proposed method offers an average accuracy of about 97 %, sensitivity of 99 %, specificity of 86 %, and predictive value of 98 %, which is superior to various well-known techniques.
    Matched MeSH terms: Image Enhancement/methods*
  2. 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
  3. 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
  4. Pasha MF, Hong KS, Rajeswari M
    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
  5. Ihtatho D, Fadzil MH, Affandi AM, Hussein SH
    PMID: 18002738
    Psoriasis is a skin disorder which is caused by genetic fault. There is no cure for psoriasis, however, there are many treatment modalities to help control the disease. To evaluate treatment efficacy, PASI (Psoriasis Area and Severity Index) which is the current gold standard method is used to measure psoriasis severity by evaluating the area, erythema, scaliness and thickness of the plaques. However, the calculation of PASI can be tedious and subjective. In this work, we develop a computer vision method that determines one of the PASI parameter, the lesion area. The method isolates healthy (or healed) skin areas from lesion areas by analyzing the hue and chroma information in the CIE L*a*b* colour space. Centroids of healthy skin and psoriasis in the hue-chroma space are determined from selected sample. Euclidean distance of all pixels from each centroid is calculated. Each pixel is assigned to the class with minimum Euclidean distance. The study involves patients from three different ethnic origins having different skin tones. Results obtained show that the proposed method is comparable to the dermatologist visual approach.
    Matched MeSH terms: Image Enhancement/methods
  6. Nugroho H, Fadzil MH, Yap VV, Norashikin S, Suraiya HH
    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
  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: Radiographic Image Enhancement/methods*
  8. Hani AF, Prakasa E, Nugroho H, Affandi AM, Hussein SH
    PMID: 23366902 DOI: 10.1109/EMBC.2012.6346941
    Psoriasis is a common skin disorder with a prevalence of 0.6 - 4.8% around the world. The most common is plaques psoriasis and it appears as red scaling plaques. Psoriasis is incurable but treatable in a long term treatment. Although PASI (Psoriasis Area and Severity Index) scoring is recognised as gold standard for psoriasis assessment, this method is still influenced by inter and intra-rater variation. An imaging and analysis system called α-PASI is developed to perform PASI scoring objectively. Percentage of lesion area to the body surface area is one of PASI parameter. In this paper, enhanced imaging methods are developed to improve the determination of body surface area (BSA) and lesion area. BSA determination method has been validated on medical mannequin. BSA accuracies obtained at four body regions are 97.80% (lower limb), 92.41% (trunk), 87.72% (upper limb), and 83.82% (head). By applying fuzzy c-means clustering algorithm, the membership functions of lesions area for PASI area scoring have been determined. Performance of scoring result has been tested with double assessment by α-PASI area algorithm on body region images from 46 patients. Kappa coefficients for α-PASI system are greater than or equal to 0.72 for all body regions (Head - 0.76, Upper limb - 0.81, Trunk - 0.85, Lower limb - 0.72). The overall kappa coefficient for the α-PASI area is 0.80 that can be categorised as substantial agreement. This shows that the α-PASI area system has a high reliability and can be used in psoriasis area assessment.
    Matched MeSH terms: Image Enhancement/methods
  9. 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*
  10. Loh KB, Ramli N, Tan LK, Roziah M, Rahmat K, Ariffin H
    Eur Radiol, 2012 Jul;22(7):1413-26.
    PMID: 22434420 DOI: 10.1007/s00330-012-2396-3
    OBJECTIVES: The degree and status of white matter myelination can be sensitively monitored using diffusion tensor imaging (DTI). This study looks at the measurement of fractional anistropy (FA) and mean diffusivity (MD) using an automated ROI with an existing DTI atlas.

    METHODS: Anatomical MRI and structural DTI were performed cross-sectionally on 26 normal children (newborn to 48 months old), using 1.5-T MRI. The automated processing pipeline was implemented to convert diffusion-weighted images into the NIfTI format. DTI-TK software was used to register the processed images to the ICBM DTI-81 atlas, while AFNI software was used for automated atlas-based volumes of interest (VOIs) and statistical value extraction.

    RESULTS: DTI exhibited consistent grey-white matter contrast. Triphasic temporal variation of the FA and MD values was noted, with FA increasing and MD decreasing rapidly early in the first 12 months. The second phase lasted 12-24 months during which the rate of FA and MD changes was reduced. After 24 months, the FA and MD values plateaued.

    CONCLUSION: DTI is a superior technique to conventional MR imaging in depicting WM maturation. The use of the automated processing pipeline provides a reliable environment for quantitative analysis of high-throughput DTI data.

    KEY POINTS: Diffusion tensor imaging outperforms conventional MRI in depicting white matter maturation. • DTI will become an important clinical tool for diagnosing paediatric neurological diseases. • DTI appears especially helpful for developmental abnormalities, tumours and white matter disease. • An automated processing pipeline assists quantitative analysis of high throughput DTI data.

    Matched MeSH terms: Image Enhancement/methods
  11. 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*
  12. Alhabshi SM, Rahmat K, Abdul Halim N, Aziz S, Radhika S, Gan GC, et al.
    Ultrasound Med Biol, 2013 Apr;39(4):568-78.
    PMID: 23384468 DOI: 10.1016/j.ultrasmedbio.2012.10.016
    The purpose of this study was to evaluate the diagnostic value of qualitative and semi-quantitative assessment of ultrasound elastography in differentiating between benign and malignant breast lesions. This prospective study was conducted in two tertiary medical centers. Consecutive B-mode ultrasound and real-time elastographic images were obtained for 67 malignant and 101 benign breast lesions in 168 women. Four experienced radiologists analyzed B-mode ultrasound alone and B-mode ultrasound combined with elastography independently. Conventional ultrasound findings were classified according to the American College of Radiology Breast Imaging Reporting and Data System classification. The elastographic assessment was based on qualitative and semi-quantitative parameters (i.e., strain pattern, width ratio, strain ratio). The sensitivity and specificity of combined elastography and conventional ultrasound were significantly higher than that of conventional ultrasound alone. The sensitivity, specificity, positive predictive value and negative predictive value was 97%, 61.4%, 62.5% and 96.8%, respectively, for conventional ultrasound and 100%, 93%, 99% and 90%, respectively, for combined technique. The semi-quantitative assessment with strain ratio and width ratio in elastography were the most useful parameters in differentiating between benign and malignant breast lesions. Cut-off point values for width ratio of more than 1.1 and strain ratio of more than 5.6 showed a high predictive value of malignancy with specificities of 84% and 76%, respectively (p 
    Matched MeSH terms: Image Enhancement/methods
  13. 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*
  14. Kamel NS, Sayeed S, Ellis GA
    IEEE Trans Pattern Anal Mach Intell, 2008 Jun;30(6):1109-13.
    PMID: 18421114 DOI: 10.1109/TPAMI.2008.32
    Utilizing the multiple degrees of freedom offered by the data glove for each finger and the hand, a novel on-line signature verification system using the Singular Value Decomposition (SVD) numerical tool for signature classification and verification is presented. The proposed technique is based on the Singular Value Decomposition in finding r singular vectors sensing the maximal energy of glove data matrix A, called principal subspace, so the effective dimensionality of A can be reduced. Having modeled the data glove signature through its r-principal subspace, signature authentication is performed by finding the angles between the different subspaces. A demonstration of the data glove is presented as an effective high-bandwidth data entry device for signature verification. This SVD-based signature verification technique is tested and its performance is shown to be able to recognize forgery signatures with a false acceptance rate of less than 1.2%.
    Matched MeSH terms: Image Enhancement/methods
  15. 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
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