Journal of Biomedical Science and Engineering

Journal of Biomedical Science and Engineering

ISSN Print: 1937-6871
ISSN Online: 1937-688X
www.scirp.org/journal/jbise
E-mail: jbise@scirp.org
"Retinal vasculature enhancement using independent component analysis"
written by Ahmad Fadzil M. Hani, Hanung Adi Nugroho,
published by Journal of Biomedical Science and Engineering, Vol.2 No.7, 2009
has been cited by the following article(s):
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[6] Swarm intelligence based adaptive gamma corrected (SIAGC) retinal image enhancement technique for early detection of Diabetic Retinopathy
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[9] Information System for Early Diabetic Retinopathy Diagnostics Based on Multiscale Texture Gradient Method
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[10] Laura Juliana Uribe Valencia
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[11] NuI-Go: Recursive Non-Local Encoder-Decoder Network for Retinal Image Non-Uniform Illumination Removal
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[12] Performance of Image Enhancement Methods for Diabetic Retinopathy based on Retinal Fundus Image
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[13] Color retinal image enhancement using luminosity and quantile based contrast enhancement
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[14] Noise identification and removal by using higher order statistics and ICA Transformation for satellite images
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[15] Image Enhancement using NHSI Model Employed in Color Retinal Images
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[16] Colour retinal images enhancement using modified histogram equalisation methods and firefly algorithm
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[17] Diagnosticul retinopatiei diabetice, bazat pe analiza comparativă a depigmentării zonei maculare: studiu experimental
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[18] Color Retinal Image Enhancement Based on Luminosity and Contrast Adjustment
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[19] ПАТОГЕНЕТИЧНЕ ОБҐРУНТУВАННЯ МЕТОДІВ АКТИВАЦІЇ СТРУКТУР ГОЛОВНОГО МОЗКУ В КОМПЛЕКСНОМУ ЛІКУВАННІ ДІАБЕТИЧНОЇ РЕТИНОПАТІЇ
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[20] Detection of Exudates in Digital Fundus Image for Diabetic Retinopathy
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[21] Implementation of Diabetic Retinopathy Detection System for Enhance Digital Fundus Images
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[22] Diabetic Retinopathy Detection Using Enhance Digital fundus Images
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[23] Sistem Monitoring dan Diagnosis Diabetic Retinopathy
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[24] Применение метода многомасштабного текстурного градиента в автоматизации диагностики диабетической ретинопатии по цифровым снимкам глазного …
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[26] Feature selection and classification approaches for biometric and biomedical applications
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[27] Methods to enhance digital fundus image for diabetic retinopathy detection
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[28] Retinal vessel enhancement based on multi-scale top-hat transformation and histogram fitting stretching
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[29] Применение метода многомасштабного текстурного градиента в автоматизации диагностики диабетической ретинопатии по цифровым снимкам глазного …
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[30] Application of the method of multiscale textural gradient for automatization of diabetesretinopathy diagnosis via analysis of digital images of the eye fundus
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[31] Joint a Retinex-based variational model and CLAHE-in-CIELUV for enhancement
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[32] Modern optical methods for retinal imaging
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[33] 一种新的视网膜血管图像增强方法
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[34] Analysis of retinal fundus images for grading of diabetic retinopathy severity
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[35] Analysis of foveal avascular zone in colour fundus images for grading of diabetic retinopathy severity
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