Displaying publications 21 - 40 of 63 in total

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  1. Fulltext Resolution of exudative retinal detachment and regression of retinal macrocyst post-laser in Coats disease
    Munira Y, Zunaina E, Azhany Y
    Int Med Case Rep J, 2013;6:37-9.
    PMID: 23966803 DOI: 10.2147/IMCRJ.S47769
    A 15-year-old boy presented with painless progressive blurring of vision in the right eye for 1 year in duration. His visual acuity in the right eye was hand movement. The right fundus showed presence of extensive subretinal exudates at the posterior pole and a retinal macrocyst at the temporal periphery. It was associated with exudative retinal detachment at the inferior periphery of the retina. Fundus angiography revealed telangiectatic retinal vessels at the superotemporal retina. Based on clinical and angiographic findings, a diagnosis of Coats disease was made. He was treated with retinal laser photocoagulation. There was resolution of the exudative retinal detachment, reduction of subretinal exudates, and regression of the retinal macrocyst with improvement of visual acuity to 1/60 post-laser therapy.
    Matched MeSH terms: Fundus Oculi
  2. Malignant hypertension with papilledema
    Tajunisah I, Patel DK
    J Emerg Med, 2013 Jan;44(1):164-5.
    PMID: 21820265 DOI: 10.1016/j.jemermed.2011.05.042
    Matched MeSH terms: Fundus Oculi
  3. Application of different imaging modalities for diagnosis of Diabetic Macular Edema: A review
    Mookiah MR, Acharya UR, Fujita H, Tan JH, Chua CK, Bhandary SV, et al.
    Comput Biol Med, 2015 Nov 1;66:295-315.
    PMID: 26453760 DOI: 10.1016/j.compbiomed.2015.09.012
    Diabetic Macular Edema (DME) is caused by accumulation of extracellular fluid from hyperpermeable capillaries within the macula. DME is one of the leading causes of blindness among Diabetes Mellitus (DM) patients. Early detection followed by laser photocoagulation can save the visual loss. This review discusses various imaging modalities viz. biomicroscopy, Fluorescein Angiography (FA), Optical Coherence Tomography (OCT) and colour fundus photographs used for diagnosis of DME. Various automated DME grading systems using retinal fundus images, associated retinal image processing techniques for fovea, exudate detection and segmentation are presented. We have also compared various imaging modalities and automated screening methods used for DME grading. The reviewed literature indicates that FA and OCT identify DME related changes accurately. FA is an invasive method, which uses fluorescein dye, and OCT is an expensive imaging method compared to fundus photographs. Moreover, using fundus images DME can be identified and automated. DME grading algorithms can be implemented for telescreening. Hence, fundus imaging based DME grading is more suitable and affordable method compared to biomicroscopy, FA, and OCT modalities.
    Matched MeSH terms: Fundus Oculi
  4. Novel risk index for the identification of age-related macular degeneration using radon transform and DWT features
    Acharya UR, Mookiah MR, Koh JE, Tan JH, Noronha K, Bhandary SV, et al.
    Comput Biol Med, 2016 06 01;73:131-40.
    PMID: 27107676 DOI: 10.1016/j.compbiomed.2016.04.009
    Age-related Macular Degeneration (AMD) affects the central vision of aged people. It can be diagnosed due to the presence of drusen, Geographic Atrophy (GA) and Choroidal Neovascularization (CNV) in the fundus images. It is labor intensive and time-consuming for the ophthalmologists to screen these images. An automated digital fundus photography based screening system can overcome these drawbacks. Such a safe, non-contact and cost-effective platform can be used as a screening system for dry AMD. In this paper, we are proposing a novel algorithm using Radon Transform (RT), Discrete Wavelet Transform (DWT) coupled with Locality Sensitive Discriminant Analysis (LSDA) for automated diagnosis of AMD. First the image is subjected to RT followed by DWT. The extracted features are subjected to dimension reduction using LSDA and ranked using t-test. The performance of various supervised classifiers namely Decision Tree (DT), Support Vector Machine (SVM), Probabilistic Neural Network (PNN) and k-Nearest Neighbor (k-NN) are compared to automatically discriminate to normal and AMD classes using ranked LSDA components. The proposed approach is evaluated using private and public datasets such as ARIA and STARE. The highest classification accuracy of 99.49%, 96.89% and 100% are reported for private, ARIA and STARE datasets. Also, AMD index is devised using two LSDA components to distinguish two classes accurately. Hence, this proposed system can be extended for mass AMD screening.
    Matched MeSH terms: Fundus Oculi
  5. Visual Vignette
    Ratnasingam J, Chooi KC, Samsuddin S, Paramasivam S, Ibrahim L, Lim LL, et al.
    Endocr Pract, 2017 Jun;23(6):752.
    PMID: 27967223 DOI: 10.4158/EP161568.VV
    Matched MeSH terms: Fundus Oculi
  6. Fulltext Neonatal eye screening for 203 healthy term new-borns using a wide-field digital retinal imaging system
    Teow Kheng Leong K, Abu Kassim SNA, Sidhu JK, Zohari Z, Sivalingam T, Ramasamy S, et al.
    BMC Ophthalmol, 2021 Mar 09;21(1):128.
    PMID: 33750348 DOI: 10.1186/s12886-021-01882-x
    BACKGROUND: The current practice for new-born eye examination by an Ophthalmologist in Malaysian hospitals is limited to only preterm new-borns, syndromic or ill infants. Healthy term new-borns are usually discharged without a thorough eye examination. This study is aimed at determining the proportion and types of ocular abnormalities detected in purportedly healthy term new-borns.

    METHOD: This cross-sectional study is comprised of 203 participants, all purportedly healthy term new-born infants from the Obstetrics and Gynaecology ward at Hospital Kuala Lumpur over a 6 months period. The examination list includes external eye examination, red reflex test, and fundus imaging using a wide-field digital retinal imaging system (Phoenix Clinical ICON Paediatric Retinal Camera) by a trained Investigator. The pathologies detected were documented. The results were compared and correlated with similar studies published in the literature previously.

    RESULTS: Total ocular abnormalities were detected in 34% of the infants. The most common finding was retinal haemorrhage in 29.6% of the infants, of which 53.3% occurred bilaterally. Spontaneous vaginal delivery (SVD) remained the greatest risk factor which has nearly 3.5 times higher risk of new-borns developing retinal haemorrhage compared to Lower Segment Caesarean Section (LSCS). There was a 6% increased likelihood of developing retinal haemorrhage for every 1-min increment in the duration of 2nd stage of labour.

    CONCLUSION: Universal eye screening for all new-borns using a wide-field digital imaging system is realistically possible, safe, and useful in detecting posterior segment disorders. The most common abnormality detected is retinal haemorrhage.

    Matched MeSH terms: Fundus Oculi
  7. Fulltext Single intravitreal ranibizumab for myopic choroidal neovascularization
    Nor-Masniwati S, Shatriah I, Zunaina E
    Clin Ophthalmol, 2011;5:1079-82.
    PMID: 21847340 DOI: 10.2147/OPTH.S21057
    We report a case of myopic choroidal neovascularization that showed improvement after a single injection of ranibizumab. A 45-year-old Chinese man with high myopia presented with sudden onset painless central scotoma of his right eye of 2 weeks' duration. There was no history of trauma. His right eye vision on presentation was 6/30 which showed no improvement with pinhole. The right fundus showed myopic maculopathy at the posterior pole with subretinal hemorrhage at the inferotemporal fovea. The optic disc was tilted with inferotemporal peripapillary atrophy. There was a myopic maculopathy appearance in the macula of the left eye. Fundus fluorescein angiography revealed choroidal neovascularization at the fovea of the right eye. A diagnosis of right eye choroidal neovascularization secondary to myopic maculopathy was made. A single intravitreal injection of ranibizumab 0.05 mL was given. Ten weeks following intravitreal injection, vision had improved to 6/7.5, and repeated fundus fluorescein angiography showed absence of choroidal neovascularization. Follow-up at 6 months showed visual acuity had normalized to 6/6 with glasses, which was maintained up to 12 months following treatment. The right fundus showed no further subretinal hemorrhage with no new lesions.
    Matched MeSH terms: Fundus Oculi
  8. Automated diabetic macular edema (DME) grading system using DWT, DCT Features and maculopathy index
    Acharya UR, Mookiah MRK, Koh JEW, Tan JH, Bhandary SV, Rao AK, et al.
    Comput Biol Med, 2017 05 01;84:59-68.
    PMID: 28343061 DOI: 10.1016/j.compbiomed.2017.03.016
    The cause of diabetic macular edema (DME) is due to prolonged and uncontrolled diabetes mellitus (DM) which affects the vision of diabetic subjects. DME is graded based on the exudate location from the macula. It is clinically diagnosed using fundus images which is tedious and time-consuming. Regular eye screening and subsequent treatment may prevent the vision loss. Hence, in this work, a hybrid system based on Radon transform (RT), discrete wavelet transform (DWT) and discrete cosine transform (DCT) are proposed for an automated detection of DME. The fundus images are subjected to RT to obtain sinograms and DWT is applied on these sinograms to extract wavelet coefficients (approximate, horizontal, vertical and diagonal). DCT is applied on approximate coefficients to obtain 2D-DCT coefficients. Further, these coefficients are converted into 1D vector by arranging the coefficients in zig-zag manner. This 1D signal is subjected to locality sensitive discriminant analysis (LSDA). Finally, various supervised classifiers are used to classify the three classes using significant features. Our proposed technique yielded a classification accuracy of 100% and 97.01% using two and seven significant features for private and public (MESSIDOR) databases respectively. Also, a maculopathy index is formulated with two significant parameters to discriminate the three groups distinctly using a single integer. Hence, our obtained results suggest that this system can be used as an eye screening tool for diabetic subjects for DME.
    Matched MeSH terms: Fundus Oculi
  9. Fulltext Bilateral profound visual loss as a consequence of leukaemia – a case report
    Raajini, Devi K., Safinaz, M.K., Hazlita, M.I.
    Journal of Surgical Academia, 2015;5(1):61-63.
    MyJurnal
    An 18-year-old Malay gentleman was noted to have profound bilateral blurred vision for one month duration, associated with loss of weight, appetite, low grade fever and abdominal distension. Visual acuity on presentation was 6/60 on the right, counting finger on the left with no afferent pupillary defect. Anterior segments were unremarkable. Vitreous cells were occasional bilaterally. Fundus revealed multiple choroidal and sub-retinal Roth spots with areas of pre-retinal and intra-retinal haemorrhages, involving the macula in the left eye. Vessels were dilated and tortuous in all quadrants of the right eye. Many areas of capillary fall out at peripheral retina were demonstrated in fundus fluorescein angiogram. Further systemic and laboratory review confirmed the diagnosis of CML and chemotherapy was initiated. Both eye ischaemic retinopathy secondary to CML was confirmed and scatter pan retinal photocoagulation was performed bilaterally. Good improvement in vision noted during subsequent follow up to 6/24 on the right, 6/60 on the left. High levels of suspicion and accurate early recognition of fundus changes are vital in these types of cases to ensure the institution of prompt treatment.
    Matched MeSH terms: Fundus Oculi
  10. Fulltext Flourescein angiogram and funduscopic features of radiation induced retinopathy: a descriptive value of retinopathy severity in patients with nasopharyngeal carcinoma
    Norshamsiah, M.D., Wan Haslina Wah, Kok, H.S., Sharifa Ezat, W.P., Fuad, I.
    Medicine & Health, 2015;10(1):23-31.
    MyJurnal
    Radiation retinopathy (RR) is a known complication after radiotherapy for Nasopharyngeal Carcinoma (NPC). This study aims to relate the relationship of RR and radiation dose in patients with NPC through assessment with clinical
    funduscopy and fundus fluorescein angiogram (FFA). A cross sectional study was conducted on patients with NPC who had completed radiotherapy treatment in the Oncology Clinic, Universiti Kebangsaan Malaysia Medical Centre (UKMMC). Eighty two eyes of 42 patients were examined and the prevalence of RR was found to be 35.4%. The severity of RR is strongly associated with the dose of radiation to the retina (Spearman correlation value=0.48; p<0.001). The common features of RR assessed by FFA were telangiectatic vessels (26.2%) and capillary non-perfusion (14.3%). Retinal neovasularization occurred in 10.7% of eyes. The level of visual deterioration correlated with the severity of RR with 26% of eyes experiencing a visual acuity of 6/18 or worse. More than one third of patients developed RR, with radiation maculopathy being the commonest cause for significant visual loss. FFA is a useful tool in detecting early signs of radiation retinopathy and maculopathy.
    Keywords: nasopharyngeal carcinoma, fluorescein fundus angiography, retinopathy, radiotherapy
    Study site: Oncology Clinic, Pusat Perubatan Universiti Kebangsaan Malaysia (PPUKM), Kuala Lumpur, Malaysia
    Matched MeSH terms: Fundus Oculi
  11. Retinal image analysis for disease screening through local tetra patterns
    Porwal P, Pachade S, Kokare M, Giancardo L, Mériaudeau F
    Comput Biol Med, 2018 11 01;102:200-210.
    PMID: 30308336 DOI: 10.1016/j.compbiomed.2018.09.028
    Age-related Macular Degeneration (AMD) and Diabetic Retinopathy (DR) are the most prevalent diseases responsible for visual impairment in the world. This work investigates discrimination potential in the texture of color fundus images to distinguish between diseased and healthy cases by avoiding the prior lesion segmentation step. It presents a retinal background characterization approach and explores the potential of Local Tetra Patterns (LTrP) for texture classification of AMD, DR and Normal images. Five different experiments distinguishing between DR - normal, AMD - normal, DR - AMD, pathological - normal and AMD - DR - normal cases were conducted and validated using the proposed approach, and promising results were obtained. For all five experiments, different classifiers namely, AdaBoost, c4.5, logistic regression, naive Bayes, neural network, random forest and support vector machine were tested. We experimented with three public datasets, ARIA, STARE and E-Optha. Further, the performance of LTrP is compared with other texture descriptors, such as local phase quantization, local binary pattern and local derivative pattern. In all cases, the proposed method obtained the area under the receiver operating characteristic curve and f-score values higher than 0.78 and 0.746 respectively. It was found that both performance measures achieve over 0.995 for DR and AMD detection using a random forest classifier. The obtained results suggest that the proposed technique can discriminate retinal disease using texture information and has potential to be an important component for an automated screening solution for retinal images.
    Matched MeSH terms: Fundus Oculi
  12. Automatic tracing of optic disc and exudates from color fundus images using fixed and variable thresholds
    Reza AW, Eswaran C, Hati S
    J Med Syst, 2009 Feb;33(1):73-80.
    PMID: 19238899
    The detection of bright objects such as optic disc (OD) and exudates in color fundus images is an important step in the diagnosis of eye diseases such as diabetic retinopathy and glaucoma. In this paper, a novel approach to automatically segment the OD and exudates is proposed. The proposed algorithm makes use of the green component of the image and preprocessing steps such as average filtering, contrast adjustment, and thresholding. The other processing techniques used are morphological opening, extended maxima operator, minima imposition, and watershed transformation. The proposed algorithm is evaluated using the test images of STARE and DRIVE databases with fixed and variable thresholds. The images drawn by human expert are taken as the reference images. The proposed method yields sensitivity values as high as 96.7%, which are better than the results reported in the literature.
    Matched MeSH terms: Fundus Oculi*
  13. Fulltext Sensitivity and specificity of automated analysis of single-field non-mydriatic fundus photographs by Bosch DR Algorithm-Comparison with mydriatic fundus photography (ETDRS) for screening in undiagnosed diabetic retinopathy
    Bawankar P, Shanbhag N, K SS, Dhawan B, Palsule A, Kumar D, et al.
    PLoS One, 2017;12(12):e0189854.
    PMID: 29281690 DOI: 10.1371/journal.pone.0189854
    Diabetic retinopathy (DR) is a leading cause of blindness among working-age adults. Early diagnosis through effective screening programs is likely to improve vision outcomes. The ETDRS seven-standard-field 35-mm stereoscopic color retinal imaging (ETDRS) of the dilated eye is elaborate and requires mydriasis, and is unsuitable for screening. We evaluated an image analysis application for the automated diagnosis of DR from non-mydriatic single-field images. Patients suffering from diabetes for at least 5 years were included if they were 18 years or older. Patients already diagnosed with DR were excluded. Physiologic mydriasis was achieved by placing the subjects in a dark room. Images were captured using a Bosch Mobile Eye Care fundus camera. The images were analyzed by the Retinal Imaging Bosch DR Algorithm for the diagnosis of DR. All subjects also subsequently underwent pharmacological mydriasis and ETDRS imaging. Non-mydriatic and mydriatic images were read by ophthalmologists. The ETDRS readings were used as the gold standard for calculating the sensitivity and specificity for the software. 564 consecutive subjects (1128 eyes) were recruited from six centers in India. Each subject was evaluated at a single outpatient visit. Forty-four of 1128 images (3.9%) could not be read by the algorithm, and were categorized as inconclusive. In four subjects, neither eye provided an acceptable image: these four subjects were excluded from the analysis. This left 560 subjects for analysis (1084 eyes). The algorithm correctly diagnosed 531 of 560 cases. The sensitivity, specificity, and positive and negative predictive values were 91%, 97%, 94%, and 95% respectively. The Bosch DR Algorithm shows favorable sensitivity and specificity in diagnosing DR from non-mydriatic images, and can greatly simplify screening for DR. This also has major implications for telemedicine in the use of screening for retinopathy in patients with diabetes mellitus.

    Study site: India
    Matched MeSH terms: Fundus Oculi*
  14. Automated diagnosis of Age-related Macular Degeneration using greyscale features from digital fundus images
    Mookiah MR, Acharya UR, Koh JE, Chandran V, Chua CK, Tan JH, et al.
    Comput Biol Med, 2014 Oct;53:55-64.
    PMID: 25127409 DOI: 10.1016/j.compbiomed.2014.07.015
    Age-related Macular Degeneration (AMD) is one of the major causes of vision loss and blindness in ageing population. Currently, there is no cure for AMD, however early detection and subsequent treatment may prevent the severe vision loss or slow the progression of the disease. AMD can be classified into two types: dry and wet AMDs. The people with macular degeneration are mostly affected by dry AMD. Early symptoms of AMD are formation of drusen and yellow pigmentation. These lesions are identified by manual inspection of fundus images by the ophthalmologists. It is a time consuming, tiresome process, and hence an automated diagnosis of AMD screening tool can aid clinicians in their diagnosis significantly. This study proposes an automated dry AMD detection system using various entropies (Shannon, Kapur, Renyi and Yager), Higher Order Spectra (HOS) bispectra features, Fractional Dimension (FD), and Gabor wavelet features extracted from greyscale fundus images. The features are ranked using t-test, Kullback-Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance (CBBD), Receiver Operating Characteristics (ROC) curve-based and Wilcoxon ranking methods in order to select optimum features and classified into normal and AMD classes using Naive Bayes (NB), k-Nearest Neighbour (k-NN), Probabilistic Neural Network (PNN), Decision Tree (DT) and Support Vector Machine (SVM) classifiers. The performance of the proposed system is evaluated using private (Kasturba Medical Hospital, Manipal, India), Automated Retinal Image Analysis (ARIA) and STructured Analysis of the Retina (STARE) datasets. The proposed system yielded the highest average classification accuracies of 90.19%, 95.07% and 95% with 42, 54 and 38 optimal ranked features using SVM classifier for private, ARIA and STARE datasets respectively. This automated AMD detection system can be used for mass fundus image screening and aid clinicians by making better use of their expertise on selected images that require further examination.
    Matched MeSH terms: Fundus Oculi
  15. Fulltext Intraocular nematode with diffuse unilateral subacute neuroretinitis: case report
    Yusoff M, Alwi AA, Said MM, Zakariah S, Ghani ZA, Zunaina E
    BMC Ophthalmol, 2011;11:15.
    PMID: 21679403 DOI: 10.1186/1471-2415-11-15
    Live intraocular nematode is a rare occurrence. Nematode can migrate actively within the eye, creating visual symptoms and damaging ocular tissue.
    Matched MeSH terms: Fundus Oculi
  16. Analysis of retinal fundus images for grading of diabetic retinopathy severity
    Ahmad Fadzil MH, Izhar LI, Nugroho H, Nugroho HA
    Med Biol Eng Comput, 2011 Jun;49(6):693-700.
    PMID: 21271293 DOI: 10.1007/s11517-011-0734-2
    Diabetic retinopathy (DR) is a sight threatening complication due to diabetes mellitus that affects the retina. In this article, a computerised DR grading system, which digitally analyses retinal fundus image, is used to measure foveal avascular zone. A v-fold cross-validation method is applied to the FINDeRS database to evaluate the performance of the DR system. It is shown that the system achieved sensitivity of >84%, specificity of >97% and accuracy of >95% for all DR stages. At high values of sensitivity (>95%), specificity (>97%) and accuracy (>98%) obtained for No DR and severe NPDR/PDR stages, the computerised DR grading system is suitable for early detection of DR and for effective treatment of severe cases.
    Matched MeSH terms: Fundus Oculi
  17. Fulltext Ocular Tuberculosis Initially Presenting as Central Retinal Vein Occlusion
    Mahyudin M, Choo MM, Ramli NM, Omar SS
    Case Rep Ophthalmol, 2010 Aug 02;1(1):30-35.
    PMID: 21116342
    A 23-year-old man presented with central retinal vein occlusion. The retinal haemorrhages worsened and signs of retinal vasculitis appeared later as vision dropped from 6/60 to Counting Fingers. No signs of systemic disease were observed. Routine Mantoux test and chest radiograph were negative for tuberculosis. Fundus flourescein angiogram confirmed presence of retinal vasculitis. Both systemic and topical corticosteroid therapy were ineffective. Polymerase chain reaction analysis of vitreous fluid showed presence of Mycobacterium tuberculosis. A full 6-month course of antituberculosis therapy was given and inflammation subsided. Vision improved to 3/60. This is a rare case of ocular tuberculosis without evidence of systemic infection, presenting first as a central retinal vein occlusion.
    Matched MeSH terms: Fundus Oculi
  18. Fulltext Prevalence of diabetic retinopathy in a primary care setting using digital retinal imaging technology
    Keah SH, Ch'ng KS
    Malays Fam Physician, 2006;1(1):19-22.
    PMID: 26998203 MyJurnal
    The objective of this study was to determine the prevalence of diabetic retinopathy in a primary care setting using digital retinal imaging technology and to quantify the degree of diabetic retinopathy using internationally accepted severity scales. Two hundred patients with type 2 diabetes were evaluated clinically followed by fundus photography. The prevalence of retinopathy and maculopathy was 47.4% and 59.2% respectively (both retinopathy and maculopathy 34.7%). The high prevalence of retinal abnormality in this study is a cause for concern as most patients had diabetes for only 5 years or less.
    Matched MeSH terms: Fundus Oculi
  19. Fulltext Neuroretinitis with dual infections
    Kiu KH, Hanizasurana H, Zunaina E
    Int Med Case Rep J, 2015;8:255-8.
    PMID: 26527902 DOI: 10.2147/IMCRJ.S91323
    A 22-year-old Malay female presented with left eye floaters for 2 weeks, associated with temporal visual field defect and metamorphopsia for 3 days. She has a guinea pig and a hedgehog at home, but denied being bitten or scratched by them. Her visual acuity at presentation was 6/12 on the left eye and 6/6 on the right eye. Her left eye relative afferent pupillary defect was barely positive with mild anterior chamber reaction. Fundus examination of the left eye showed mild vitritis, swollen optic disc with macular star, crops of active choroidal lesions at superonasal retina with a linear arrangement in the form of migratory track nasally. However, there were no nematodes seen on fundus examination. Investigations showed normal full blood count with no eosinophilia and positive serology test for Bartonella henselae. She was diagnosed to have dual infection - diffuse unilateral subacute neuroretinitis (DUSN), based on the presence of crops of choroidal lesions with migratory track, and cat scratch disease (CSD) based on a positive serological test. She was treated with oral albendazole 400 mg 12 hourly for 6 weeks for DUSN and oral doxycycline 100 mg 12 hourly for 4 weeks for CSD. Focal laser had been applied to the area of migratory track in the left eye. Her left eye vision improved to 6/6 at 1 month after treatment, with resolution of neuroretinitis.
    Matched MeSH terms: Fundus Oculi
  20. Fulltext Automated microaneurysm detection in diabetic retinopathy using curvelet transform
    Ali Shah SA, Laude A, Faye I, Tang TB
    J Biomed Opt, 2016 Oct;21(10):101404.
    PMID: 26868326 DOI: 10.1117/1.JBO.21.10.101404
    Microaneurysms (MAs) are known to be the early signs of diabetic retinopathy (DR). An automated MA detection system based on curvelet transform is proposed for color fundus image analysis. Candidates of MA were extracted in two parallel steps. In step one, blood vessels were removed from preprocessed green band image and preliminary MA candidates were selected by local thresholding technique. In step two, based on statistical features, the image background was estimated. The results from the two steps allowed us to identify preliminary MA candidates which were also present in the image foreground. A collection set of features was fed to a rule-based classifier to divide the candidates into MAs and non-MAs. The proposed system was tested with Retinopathy Online Challenge database. The automated system detected 162 MAs out of 336, thus achieved a sensitivity of 48.21% with 65 false positives per image. Counting MA is a means to measure the progression of DR. Hence, the proposed system may be deployed to monitor the progression of DR at early stage in population studies.
    Matched MeSH terms: Fundus Oculi
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