Displaying all 8 publications

  1. Aljarousha M, Badarudin NE, Che Azemin MZ
    Malays J Med Sci, 2016 May;23(3):72-7.
    PMID: 27418872 MyJurnal
    INTRODUCTION: Diabetes may affect the human body's systems and organs, including the eye. Diabetic retinopathy is the 5th leading cause of blindness globally. Diabetic subjects demonstrated dry eye symptoms that were also supported by the low values of the clinical tests.
    PURPOSE: This study aimed to compare the dry eye symptoms and signs between diabetics and non-diabetics and tear functions between diabetic subjects with and without dry eye.
    METHODS: This retrospective study was based on the observation of 643 medical files. Using a convenience sampling method, 88 subjects were found to report diabetes mellitus. The information extracted from the files included: date of first examination, age at first visit, gender, past ocular history, systemic disease, symptoms of dry eye disease and details of clinical diagnostic signs. Non-contact lens wearers were excluded. A group of 88, age and gender matched, control subjects were included for this comparison study.
    RESULTS: The percentage of dry eye symptoms was higher in diabetic subjects (15.9%) compared with non-diabetic subjects (13.6%; p<0.001). The percentage of dry eye symptoms was also higher in diabetics with dry eye (63%) than in diabetics without dry eye (36.9%; p<0.001). Tear break up time was significantly different between diabetics and non-diabetics (p<0.001) and between diabetics with and without dry eye (p=0.046). The corneal staining was significantly different between diabetic subjects with and without dry eye (p=0.028).
    CONCLUSION: Dry eye symptoms were significantly associated with diabetics. Tear break up time was significantly shorter in diabetics with dry eye compared to diabetics without dry eye.
    KEYWORDS: Diabetes mellitus; cornea; dry eye syndromes; signs and symptoms; tears
    Study site: Klinik Kesihatan Jalan Hospital, Kuantan, Malaysia
  2. Aliahmad B, Kumar DK, Hao H, Unnikrishnan P, Che Azemin MZ, Kawasaki R, et al.
    ScientificWorldJournal, 2014;2014:467462.
    PMID: 25485298 DOI: 10.1155/2014/467462
    Fractal dimensions (FDs) are frequently used for summarizing the complexity of retinal vascular. However, previous techniques on this topic were not zone specific. A new methodology to measure FD of a specific zone in retinal images has been developed and tested as a marker for stroke prediction. Higuchi's fractal dimension was measured in circumferential direction (FDC) with respect to optic disk (OD), in three concentric regions between OD boundary and 1.5 OD diameter from its margin. The significance of its association with future episode of stroke event was tested using the Blue Mountain Eye Study (BMES) database and compared against spectrum fractal dimension (SFD) and box-counting (BC) dimension. Kruskal-Wallis analysis revealed FDC as a better predictor of stroke (H = 5.80, P = 0.016, α = 0.05) compared with SFD (H = 0.51, P = 0.475, α = 0.05) and BC (H = 0.41, P = 0.520, α = 0.05) with overall lower median value for the cases compared to the control group. This work has shown that there is a significant association between zone specific FDC of eye fundus images with future episode of stroke while this difference is not significant when other FD methods are employed.
  3. Kumar DK, Aliahmad B, Hao H, Che Azemin MZ, Kawasaki R
    ISRN Ophthalmol, 2013;2013:865834.
    PMID: 24558608 DOI: 10.1155/2013/865834
    Pulsatile changes in retinal vascular geometry over the cardiac cycle have clinical implication for diagnosis of ocular and systemic vascular diseases. In this study, we report a Vesselness Mapping of Retinal Image Sequence (VMRS) methodology to visualize the vessel pulsation and quantify the pulsatile motions in the cardiac cycle. Retinal images were recorded in an image sequence corresponding to 8 segments of the cardiac cycle using a nonmydriatic fundus camera (Canon CR45, Canon Inc., Japan) modified with ECG-synchronization. Individual cross-sectional vessel diameters were measured separately and the significance of the variations was tested statistically by repeated measures analysis of variance (ANOVA). The graders observed an improved quality of vessel pulsation on a wide region around the optic disk using the VMRS. Individual cross- sectional vessel diameter measurement after visualization of pulsatile motions resulted in the detection of more significant diameter change for both arterioles (3.3 μm, P = 0.001) and venules (6.6 μm, P < 0.001) compared to individual measurement without visualization of the pulsatile motions (all P values > 0.05), showing an increase of 2.1 μm and 4.7 μm for arterioles and venules, respectively.
  4. Che Azemin MZ, Ab Hamid F, Aminuddin A, Wang JJ, Kawasaki R, Kumar DK
    Exp Eye Res, 2013 Nov;116:355-358.
    PMID: 24512773 DOI: 10.1016/j.exer.2013.10.010
    The fractal dimension is a global measure of complexity and is useful for quantifying anatomical structures, including the retinal vascular network. A previous study found a linear declining trend with aging on the retinal vascular fractal dimension (DF); however, it was limited to the older population (49 years and older). This study aimed to investigate the possible models of the fractal dimension changes from young to old subjects (10-73 years). A total of 215 right-eye retinal samples, including those of 119 (55%) women and 96 (45%) men, were selected. The retinal vessels were segmented using computer-assisted software, and non-vessel fragments were deleted. The fractal dimension was measured based on the log-log plot of the number of grids versus the size. The retinal vascular DF was analyzed to determine changes with increasing age. Finally, the data were fitted to three polynomial models. All three models are statistically significant (Linear: R2 = 0.1270, 213 d.f., p 
  5. Ab Hamid F, Che Azemin MZ, Salam A, Aminuddin A, Mohd Daud N, Zahari I
    Curr. Eye Res., 2016 Jun;41(6):823-31.
    PMID: 26268475 DOI: 10.3109/02713683.2015.1056375
    PURPOSE: The goal of this study was to provide the empirical evidence of fractal dimension as an indirect measure of retinal vasculature density.

    MATERIALS AND METHODS: Two hundred retinal samples of right eye [57.0% females (n = 114) and 43.0% males (n = 86)] were selected from baseline visit. A custom-written software was used for vessel segmentation. Vessel segmentation is the process of transforming two-dimensional color images into binary images (i.e. black and white pixels). The circular area of approximately 2.6 optic disc radii surrounding the center of optic disc was cropped. The non-vessels fragments were removed. FracLac was used to measure the fractal dimension and vessel density of retinal vessels.

    RESULTS: This study suggested that 14.1% of the region of interest (i.e. approximately 2.6 optic disk radii) comprised retinal vessel structure. Using correlation analysis, vessel density measurement and fractal dimension estimation are linearly and strongly correlated (R = 0.942, R(2) = 0.89, p 

  6. Jusoh M, Dzulkarnain AAA, Rahmat S, Musa R, Che Azemin MZ
    Asia Pac Psychiatry, 2020 Aug 19.
    PMID: 32815284 DOI: 10.1111/appy.12414
    The aim of this study is to evaluate the psychometric properties of the Malay version of the Swanson, Nolan, and Pelham Parent Rating Scale of attention deficit hyperactivity disorders (ADHD) symptoms (M-SNAP-IV). For this purpose, the SNAP-IV scale was translated into the Malay language and was pilot-tested on 91 parents of children aged 8 to 11 years (ADHD [n = 36] and non-ADHD children [n = 55]). The findings depicted that the M-SNAP-IV has excellent content validity, internal consistency, and test-retest reliability. The M-SNAP-IV is a valid and reliable screening tool to detect ADHD symptoms in children and has the advantages to assess the specific presentation of ADHD.
  7. Che Azemin MZ, Hassan R, Mohd Tamrin MI, Md Ali MA
    PMID: 32849861 DOI: 10.1155/2020/8828855
    The key component in deep learning research is the availability of training data sets. With a limited number of publicly available COVID-19 chest X-ray images, the generalization and robustness of deep learning models to detect COVID-19 cases developed based on these images are questionable. We aimed to use thousands of readily available chest radiograph images with clinical findings associated with COVID-19 as a training data set, mutually exclusive from the images with confirmed COVID-19 cases, which will be used as the testing data set. We used a deep learning model based on the ResNet-101 convolutional neural network architecture, which was pretrained to recognize objects from a million of images and then retrained to detect abnormality in chest X-ray images. The performance of the model in terms of area under the receiver operating curve, sensitivity, specificity, and accuracy was 0.82, 77.3%, 71.8%, and 71.9%, respectively. The strength of this study lies in the use of labels that have a strong clinical association with COVID-19 cases and the use of mutually exclusive publicly available data for training, validation, and testing.
  8. Hilmi MR, Che Azemin MZ, Mohd Kamal K, Mohd Tamrin MI, Abdul Gaffur N, Tengku Sembok TM
    Curr. Eye Res., 2017 Jun;42(6):852-856.
    PMID: 28118054 DOI: 10.1080/02713683.2016.1250277
    PURPOSE: The goal of this study was to predict visual acuity (VA) and contrast sensitivity function (CSF) with tissue redness grading after pterygium surgery.

    MATERIALS AND METHODS: A total of 67 primary pterygium participants were selected from patients who visited an ophthalmology clinic. We developed a semi-automated computer program to measure the pterygium fibrovascular redness from digital pterygium images. The final outcome of this software is a continuous scale grading of 1 (minimum redness) to 3 (maximum redness). The region of interest (ROI) was selected manually using the software. Reliability was determined by repeat grading of all 67 images, and its association with CSF and VA was examined.

    RESULTS: The mean and standard deviation of redness of the pterygium fibrovascular images was 1.88 ± 0.55. Intra-grader and inter-grader reliability estimates were high with intraclass correlation ranging from 0.97 to 0.98. The new grading was positively associated with CSF (p < 0.01) and VA (p < 0.01). The redness grading was able to predict 25% and 23% of the variance in the CSF and the VA, respectively.

    CONCLUSIONS: The new grading of pterygium fibrovascular redness can be reliably measured from digital images and showed a good correlation with CSF and VA. The redness grading can be used in addition to the existing pterygium grading.
Related Terms
Contact Us

Please provide feedback to Administrator (tengcl@gmail.com)

External Links