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Artykuły w czasopismach na temat „Microaneurysms (MA)”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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Dafwen Toresa, Nor Hazlyna Harun, Juhaida Abu Bakar. "Detection of Microaneurysm Model Using Kmean Clustering Method, Hough Transform Optimization and CNN." Journal of Information Systems Engineering and Management 10, no. 1s (2024): 551–62. https://doi.org/10.52783/jisem.v10i1s.6845.

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Introduction: Diabetic retinopathy (DR) is a chronic disease that damages the retina due to damage to the small blood vessels caused by diabetes mellitus. This disease is one of the main causes of visual impairment in people with diabetes. Early detection of clinical signs of DR is essential to allow for effective intervention and treatment. Ophthalmologists are trained to recognize DR by examining small changes in the eye, such as microaneurysms, retinal hemorrhages, macular edema, and changes in the retinal blood vessels. Detection of microaneurysms (MA) plays a vital role in the early diagn

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Shamela Rizwana, M., J. Gowthamy, and P. Suganya. "True Microaneurysms Detection in Cluttered Retinal Photographs for the Detection of Diabetic Retinopathy." Journal of Computational and Theoretical Nanoscience 17, no. 4 (2020): 1985–89. http://dx.doi.org/10.1166/jctn.2020.8477.

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Microaneurysms are the first clinical sign of diabetic retinopathy. The number of microaneurysms is used to indicate the severity of the disease. Early microaneurysm detection can help reduce the incidence of blindness. This paper analyzes the Threshold based technique and Wavelet Decomposition technique to reject specific classes of noises while passing majority of true Microaneurysms using a set of specialized features. The rejection strategy is formulated based on the occurrence frequency and discriminability of the underlying clutter. Threshold based technique separates both classes and fu

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Zhou, Wei, Chengdong Wu, Dali Chen, Zhenzhu Wang, Yugen Yi, and Wenyou Du. "Automatic Microaneurysms Detection Based on Multifeature Fusion Dictionary Learning." Computational and Mathematical Methods in Medicine 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/2483137.

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Recently, microaneurysm (MA) detection has attracted a lot of attention in the medical image processing community. Since MAs can be seen as the earliest lesions in diabetic retinopathy, their detection plays a critical role in diabetic retinopathy diagnosis. In this paper, we propose a novel MA detection approach named multifeature fusion dictionary learning (MFFDL). The proposed method consists of four steps: preprocessing, candidate extraction, multifeature dictionary learning, and classification. The novelty of our proposed approach lies in incorporating the semantic relationships among mul

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Zhang, Lizong, Shuxin Feng, Guiduo Duan, Ying Li, and Guisong Liu. "Detection of Microaneurysms in Fundus Images Based on an Attention Mechanism." Genes 10, no. 10 (2019): 817. http://dx.doi.org/10.3390/genes10100817.

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Microaneurysms (MAs) are the earliest detectable diabetic retinopathy (DR) lesions. Thus, the ability to automatically detect MAs is critical for the early diagnosis of DR. However, achieving the accurate and reliable detection of MAs remains a significant challenge due to the size and complexity of retinal fundus images. Therefore, this paper presents a novel MA detection method based on a deep neural network with a multilayer attention mechanism for retinal fundus images. First, a series of equalization operations are performed to improve the quality of the fundus images. Then, based on the

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Sharma, Aditya, and Vikul Pawar. "Early Assessment of Diabetic Retinopathy by Detecting Microaneurysm with Deep Neural Network." Indian Journal Of Science And Technology 17, no. 17 (2024): 1786–90. http://dx.doi.org/10.17485/ijst/v17i17.732.

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Objectives: This study aims to detect early signs of diabetic retinopathy, also known as microaneurysm (MA). Early detection of MA can help in diagnosing diabetic retinopathy effectively. Methods: To achieve this objective a method is proposed which is based on a deep learning model that incorporates transfer learning. The dataset used in this study is E-Ophtha which consists of 381 high-quality images. The proposed model consists of three steps which are preprocessing, feature extraction and classification. The method uses CLAHE to enhance the details of the fundus image. The feature extracti

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G, R. Hemalakshmi, and B. Prakash N. "Detection of Microaneurysms in Fundus Images using ELM Classifier." International Journal of Current Pharmaceutical Review and Research 9, no. 3 (2017): 223–27. https://doi.org/10.5281/zenodo.12674394.

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The main objective of this paper is to detect the microaneurysms which is the sign and symptom for the retinal diseaseDiabetic Retinopathy (DR). In this work, the input image is preprocessed and then cross sectional scanning is applied forpeak detection and property measurement. Feature set from the processed images is extracted and ELM classifier is usedfor MA detection. The experimental results show the proposed system provides better results compared to existing system.

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G, R. Hemalakshmi, and B. Prakash N. "Detection of Microaneurysms in Fundus Images using ELM Classifier." International Journal of Current Pharmaceutical Review and Research 8, no. 3 (2017): 223–27. https://doi.org/10.5281/zenodo.12677464.

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The main objective of this paper is to detect the microaneurysms which is the sign and symptom for the retinal diseaseDiabetic Retinopathy (DR). In this work, the input image is preprocessed and then cross sectional scanning is applied forpeak detection and property measurement. Feature set from the processed images is extracted and ELM classifier is usedfor MA detection. The experimental results show the proposed system provides better results compared to existing system.

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Aditya, Sharma, and Pawar Vikul. "Early Assessment of Diabetic Retinopathy by Detecting Microaneurysm with Deep Neural Network." Indian Journal of Science and Technology 17, no. 17 (2024): 1786–90. https://doi.org/10.17485/IJST/v17i17.732.

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Abstract <strong>Objectives:</strong> This study aims to detect early signs of diabetic retinopathy, also known as microaneurysm (MA). Early detection of MA can help in diagnosing diabetic retinopathy effectively. <strong>Methods:</strong> To achieve this objective a method is proposed which is based on a deep learning model that incorporates transfer learning. The dataset used in this study is E-Ophtha which consists of 381 high-quality images. The proposed model consists of three steps which are preprocessing, feature extraction and classification. The method uses CLAHE to enh

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T. Monisha Birlin. "Automatic Detection of Microaneurysms Using Modified UNET Architecture." Journal of Information Systems Engineering and Management 10, no. 15s (2025): 131–36. https://doi.org/10.52783/jisem.v10i15s.2436.

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Increasingly, more people throughout the world are suffering from Diabetic Retinopathy (DR). A high blood glucose level damages the retina, which is found at the back of the eye and causes vision loss, leading to DR. The earliest symptoms of DR are referred to as microaneurysms (MAs). Due to their small size, dusky color, and practically round shape, these MAs are easy for ophthalmologists to overlook during physical investigation. In this situation, reliable early MA diagnosis is useful to prevent DR before irreversible blindness. The manual detection of DR is a labor-intensive and time-consu

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Li, He, Yixiang Deng, Konstantina Sampani, et al. "Computational investigation of blood cell transport in retinal microaneurysms." PLOS Computational Biology 18, no. 1 (2022): e1009728. http://dx.doi.org/10.1371/journal.pcbi.1009728.

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Microaneurysms (MAs) are one of the earliest clinically visible signs of diabetic retinopathy (DR). MA leakage or rupture may precipitate local pathology in the surrounding neural retina that impacts visual function. Thrombosis in MAs may affect their turnover time, an indicator associated with visual and anatomic outcomes in the diabetic eyes. In this work, we perform computational modeling of blood flow in microchannels containing various MAs to investigate the pathologies of MAs in DR. The particle-based model employed in this study can explicitly represent red blood cells (RBCs) and platel

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Zhang, Bowei, Jing Li, Yun Bai, Qing Jiang, Biao Yan, and Zhenhua Wang. "An Improved Microaneurysm Detection Model Based on SwinIR and YOLOv8." Bioengineering 10, no. 12 (2023): 1405. http://dx.doi.org/10.3390/bioengineering10121405.

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Diabetic retinopathy (DR) is a microvascular complication of diabetes. Microaneurysms (MAs) are often observed in the retinal vessels of diabetic patients and represent one of the earliest signs of DR. Accurate and efficient detection of MAs is crucial for the diagnosis of DR. In this study, an automatic model (MA-YOLO) is proposed for MA detection in fluorescein angiography (FFA) images. To obtain detailed features and improve the discriminability of MAs in FFA images, SwinIR was utilized to reconstruct super-resolution images. To solve the problems of missed detection of small features and f

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Kazeminasab, Elahe Sadat, Ramin Almasi, Bijan Shoushtarian, Ehsan Golkar, and Hossein Rabbani. "Automatic Detection of Microaneurysms in OCT Images Using Bag of Features." Computational and Mathematical Methods in Medicine 2022 (July 15, 2022): 1–10. http://dx.doi.org/10.1155/2022/1233068.

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Diabetic retinopathy (DR) caused by diabetes occurs as a result of changes in the retinal vessels and causes visual impairment. Microaneurysms (MAs) are the early clinical signs of DR, whose timely diagnosis can help detecting DR in the early stages of its development. It has been observed that MAs are more common in the inner retinal layers compared to the outer retinal layers in eyes suffering from DR. Optical coherence tomography (OCT) is a noninvasive imaging technique that provides a cross-sectional view of the retina, and it has been used in recent years to diagnose many eye diseases. As

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Takamura, Yoshihiro, Yutaka Yamada, and Masaru Inatani. "Role of Microaneurysms in the Pathogenesis and Therapy of Diabetic Macular Edema: A Descriptive Review." Medicina 59, no. 3 (2023): 435. http://dx.doi.org/10.3390/medicina59030435.

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Background and Objectives: This study aims to elucidate the role of microaneurysms (MAs) in the pathogenesis and treatment of diabetic retinopathy (DR) and diabetic macular edema (DME), the major causes of acquired visual impairment. Materials and Methods: We synthesized the relevance of findings on the clinical characteristics, pathogenesis, and etiology of MAs in DR and DME and their role in anti-vascular endothelial growth factor (VEGF) therapy. Results: MAs, a characteristic feature in DR and DME, can be detected by fluorescein angiography, optical coherence tomography (OCT) and OCT angiog

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de Mello, Vanessa Derenji, Tuomas Selander, Jaana Lindström, Jaakko Tuomilehto, Matti Uusitupa, and Kai Kaarniranta. "Serum Levels of Plasmalogens and Fatty Acid Metabolites Associate with Retinal Microangiopathy in Participants from the Finnish Diabetes Prevention Study." Nutrients 13, no. 12 (2021): 4452. http://dx.doi.org/10.3390/nu13124452.

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Diabetic retinopathy (DR) is the most common microvascular complication of diabetes, and retinal microaneurysms (MA) are one of the first detected abnormalities associated with DR. We recently showed elevated serum triglyceride levels to be associated with the development of MA in the Finnish Diabetes Prevention Study (DPS). The purpose of this metabolomics study was to assess whether serum fatty acid (FA) composition, plasmalogens, and low-grade inflammation may enhance or decrease the risk of MA. Originally, the DPS included 522 individuals (mean 55 years old, range 40–64 years) with impaire

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Jiang, Alice, Sunil Srivastava, Natalia Figueiredo, et al. "Repeatability of automated leakage quantification and microaneurysm identification utilising an analysis platform for ultra-widefield fluorescein angiography." British Journal of Ophthalmology 104, no. 4 (2019): 500–503. http://dx.doi.org/10.1136/bjophthalmol-2019-314416.

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Background/aimsUltra-widefield fluorescein angiography (UWFA) provides unique opportunities for panretinal assessment of retinal diseases. The objective quantification of UWFA features is a labour-intensive manual process, limiting its utility. The present study assesses the consistency/repeatability of an automated assessment platform for the characterisation of retinal vascular features, quantification of microaneurysms (MA) and leakage foci in UWFA images.MethodsAn Institutional Review Board-approved retrospective image analysis study was performed on UWFA images. For each eye, two arteriov

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D. Shirbahadurkar, S., V. M. Mane, and D. V. Jadhav. "An efficient method for early stage detection of diabetic retinopathy." International Journal of Engineering & Technology 7, no. 1.1 (2017): 414. http://dx.doi.org/10.14419/ijet.v7i1.1.9945.

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Diabetic Retinopathy (DR) is one of the leading causes of blindness. The early detection and treatment of DR is significant to save the human vision. The presence of microaneurysms (MAs) is the first sign of the disease. The correct identification of MAs is an essential for finding of DR at the early stages. In this paper, we propose a three phase system for efficient recognition of MAs. The tentative MA lesions are recovered from the fundus image in the first stage. To accurately classify an extracted candidate region into MA or non-MA, the second stage prepares an attribute vector for each t

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Yamada, Yutaka, Yoshihiro Takamura, Masakazu Morioka, et al. "Characteristics of Microaneurysm Size in Residual Edema After Intravitreal Injection of Faricimab for Diabetic Macular Edema." Journal of Clinical Medicine 13, no. 24 (2024): 7839. https://doi.org/10.3390/jcm13247839.

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Background/Objectives: Microaneurysms (MAs) are important in the pathology of diabetic macular edema (DME) and its response to anti-vascular endothelial growth factor (VEGF) therapy. This study aimed to clarify the morphological characteristics of MAs in residual edema following consecutive faricimab injections, a bispecific antibody against angiopoietin-2 and VEGF. Methods: We selected patients with DME who exhibited residual edema after three monthly injections of faricimab. In both the residual and absorbed areas of edema, we counted the turnover of MAs, including those that were lost and t

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Sebastian, Anila, Omar Elharrouss, Somaya Al-Maadeed, and Noor Almaadeed. "A Survey on Diabetic Retinopathy Lesion Detection and Segmentation." Applied Sciences 13, no. 8 (2023): 5111. http://dx.doi.org/10.3390/app13085111.

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Diabetes is a global problem which impacts people of all ages. Diabetic retinopathy (DR) is a main ailment of the eyes resulting from diabetes which can result in loss of eyesight if not detected and treated on time. The current process of detecting DR and its progress involves manual examination by experts, which is time-consuming. Extracting the retinal vasculature, and segmentation of the optic disc (OD)/fovea play a significant part in detecting DR. Detecting DR lesions like microaneurysms (MA), hemorrhages (HM), and exudates (EX), helps to establish the current stage of DR. Recently with

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Rizzieri, Nicola, Luca Dall’Asta, and Maris Ozoliņš. "Diabetic Retinopathy Features Segmentation without Coding Experience with Computer Vision Models YOLOv8 and YOLOv9." Vision 8, no. 3 (2024): 48. http://dx.doi.org/10.3390/vision8030048.

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Computer vision is a powerful tool in medical image analysis, supporting the early detection and classification of eye diseases. Diabetic retinopathy (DR), a severe eye disease secondary to diabetes, accompanies several early signs of eye-threatening conditions, such as microaneurysms (MAs), hemorrhages (HEMOs), and exudates (EXs), which have been widely studied and targeted as objects to be detected by computer vision models. In this work, we tested the performances of the state-of-the-art YOLOv8 and YOLOv9 architectures on DR fundus features segmentation without coding experience or a progra

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Watanabe, Akira, Hirotugu Takashina, and Tadashi Nakano. "Effect of microaneurysms on the anti-VEGF treatment for diabetic macular edema: A retrospective cross-sectional study." Medicine 102, no. 44 (2023): e35888. http://dx.doi.org/10.1097/md.0000000000035888.

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Although anti-vascular endothelial growth factor (VEGF) treatment is effective for treating diabetic macular edema (DME), the effect of the microaneurysm (MA) status on the therapeutic efficacy of an anti-VEGF treatment remains unclear. Our current study investigated the effects of the number and the presence or absence of leaking MAs on DME and the efficacy of anti-VEGF therapy. A total of 51 eyes of 47 DME patients were administered anti-VEGF treatment. Fluorescence angiography results were used to determine the number of MAs and the presence or absence of leakage, with these findings matche

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Haj Najeeb, Bilal, Bianca S. Gerendas, Alessio Montuoro, Christian Simader, Gábor G. Deák, and Ursula M. Schmidt-Erfurth. "A Novel Effect of Microaneurysms and Retinal Cysts on Capillary Perfusion in Diabetic Macular Edema: A Multimodal Imaging Study." Journal of Clinical Medicine 14, no. 9 (2025): 2985. https://doi.org/10.3390/jcm14092985.

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Background/Objectives: The aim of this study was to investigate the potential contribution of microaneurysms (MAs) and retinal cysts to the pathogenesis of macular non-perfusion in patients with diabetic macular edema (DME) using multimodal imaging. Methods: In this cross-sectional study, 42 eyes with DME were analyzed using color fundus photography, fluorescein angiography (FA) and optical coherence tomography (OCT). Macular non-perfusion within the central 3000 µm was categorized by location and extent into foveal avascular zone enlargement (FAZE), focal non-perfusion (FNP) and diffuse non-p

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Karst, Sonja G., Jan Lammer, Salma H. Radwan, et al. "Characterization of In Vivo Retinal Lesions of Diabetic Retinopathy Using Adaptive Optics Scanning Laser Ophthalmoscopy." International Journal of Endocrinology 2018 (2018): 1–12. http://dx.doi.org/10.1155/2018/7492946.

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Purpose. To characterize hallmark diabetic retinopathy (DR) lesions utilizing adaptive optics scanning laser ophthalmoscopy (AOSLO) and to compare AOSLO findings with those on standard imaging techniques. Methods. Cross-sectional study including 35 eyes of 34 study participants. AOSLO confocal and multiply scattered light (MSL) imaging were performed in eyes with DR. Color fundus photographs (CF), infrared images of the macula (Spectralis, Heidelberg), and Spectralis spectral domain optical coherence tomography SDOCT B-scans of each lesion were obtained and registered to corresponding AOSLO im

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Purushottama, T. L., and C. Kishore. "DIAGNOSIS OF DIABETIC RETINOPATHY THROUGH SCREENING OF RETINAL IMAGES." INTERNATIONAL JOURNAL OF RESEARCH- GRANTHAALAYAH 5, no. 4 RACEEE (2017): 92–104. https://doi.org/10.5281/zenodo.580631.

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Diabetic Retinopathy (DR) is progressive dysfunction of the retinal blood vessels caused by chronic hyperglycemia which can be a complication of diabetes type 1 or diabetes type 2. Initially, DR is asymptomatic, if not treated though it can cause low vision and blindness. Diabetic retinopathy is responsible for 1.8 million of the 37 million cases of blindness throughout the world. So the early detection of Diabetic retinopathy through proper screening is essential. The paper presents a Diabetic Retinopathy Screening System which can be used as a primary diagnosis tool by ophthalmologists in th

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Rykov, S. O., K. V. Korobov, and S. Yu Mogilevskyy. "Progression of initial diabetic angiopathy: association with carbohydrate disorders." Archive of Ukrainian Ophthalmology 8, no. 3 (2021): 6–12. http://dx.doi.org/10.22141/2309-8147.8.3.2020.220448.

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Background. Recognizing the early stages of diabetic retinopathy (DR) in patients with type 2 diabetes mellitus (T2DM) and predicting their progression is important and is an urgent challenge of modern ophthalmology. The study aimed at investigating the peculiarities of occurrence and progression of DR initial studies and establishing its relationship with the severity of carbohydrate metabolism disorders in patients with T2DM. Materials and methods. We examined 91 patients (182 eyes) with T2DM. Based on the ETDRS system of clinical signs Airlie House, there were determined the microaneurysms

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Bilal, Anas, Liucun Zhu, Anan Deng, Huihui Lu, and Ning Wu. "AI-Based Automatic Detection and Classification of Diabetic Retinopathy Using U-Net and Deep Learning." Symmetry 14, no. 7 (2022): 1427. http://dx.doi.org/10.3390/sym14071427.

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Artificial intelligence is widely applied to automate Diabetic retinopathy diagnosis. Diabetes-related retinal vascular disease is one of the world’s most common leading causes of blindness and vision impairment. Therefore, automated DR detection systems would greatly benefit the early screening and treatment of DR and prevent vision loss caused by it. Researchers have proposed several systems to detect abnormalities in retinal images in the past few years. However, Diabetic Retinopathy automatic detection methods have traditionally been based on hand-crafted feature extraction from the retina

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Fernández-Espinosa, Guisela, Ana Boned-Murillo, Elvira Orduna-Hospital, et al. "Retinal Vascularization Abnormalities Studied by Optical Coherence Tomography Angiography (OCTA) in Type 2 Diabetic Patients with Moderate Diabetic Retinopathy." Diagnostics 12, no. 2 (2022): 379. http://dx.doi.org/10.3390/diagnostics12020379.

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Diabetic retinopathy (DR) is the most severe and frequent retinal vascular disease that causes significant visual loss on a global scale. The purpose of our study was to evaluate retinal vascularization in the superficial capillary plexus (SCP), the deep capillary plexus (DCP) and the choriocapillaris (CC) and changes in the foveal avascular zone (FAZ) by optical tomography angiography (OCTA) in patients with type 2 diabetes mellitus (DM2) with moderate DR but without diabetic macular oedema (DME). Fifty-four eyes of DM2 with moderate DR (level 43 in the ETDRS scale) and without DME and 73 age

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Hajdu, Dorottya, Reinhard Told, Orsolya Angeli, et al. "Identification of microvascular and morphological alterations in eyes with central retinal non-perfusion." PLOS ONE 15, no. 11 (2020): e0241753. http://dx.doi.org/10.1371/journal.pone.0241753.

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Purpose To evaluate the characteristics and morphological alterations in central retinal ischemia caused by diabetic retinopathy (DR) or retinal vein occlusion (RVO) as seen in optical coherence tomography angiography (OCTA) and their relationship to visual acuity. Methods Swept-source optical coherence tomography (SSOCT) and OCTA (Topcon, Triton) data of patients with central involving retinal ischemia were analyzed in this cross-sectional study. The following parameters were evaluated: vessel parameters, foveal avascular zone (FAZ), intraretinal cysts (IRC), microaneurysms (MA), vascular col

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Li, Feng, Shiqing Tang, Yuyang Chen, and Haidong Zou. "Deep attentive convolutional neural network for automatic grading of imbalanced diabetic retinopathy in retinal fundus images." Biomedical Optics Express 13, no. 11 (2022): 5813. http://dx.doi.org/10.1364/boe.472176.

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Automated fine-grained diabetic retinopathy (DR) grading was of great significance for assisting ophthalmologists in monitoring DR and designing tailored treatments for patients. Nevertheless, it is a challenging task as a result of high intra-class variations, high inter-class similarities, small lesions, and imbalanced data distributions. The pivotal factor for the success in fine-grained DR grading is to discern more subtle associated lesion features, such as microaneurysms (MA), Hemorrhages (HM), soft exudates (SE), and hard exudates (HE). In this paper, we constructed a simple yet effecti

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Deng, Jiakun, Puying Tang, Xuegong Zhao, Tian Pu, Chao Qu, and Zhenming Peng. "Local Structure Awareness-Based Retinal Microaneurysm Detection with Multi-Feature Combination." Biomedicines 10, no. 1 (2022): 124. http://dx.doi.org/10.3390/biomedicines10010124.

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Retinal microaneurysm (MA) is the initial symptom of diabetic retinopathy (DR). The automatic detection of MA is helpful to assist doctors in diagnosis and treatment. Previous algorithms focused on the features of the target itself; however, the local structural features of the target and background are also worth exploring. To achieve MA detection, an efficient local structure awareness-based retinal MA detection with the multi-feature combination (LSAMFC) is proposed in this paper. We propose a novel local structure feature called a ring gradient descriptor (RGD) to describe the structural d

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Pappuru, Rajeev K. R., Luísa Ribeiro, Conceição Lobo, Dalila Alves, and José Cunha-Vaz. "Microaneurysm turnover is a predictor of diabetic retinopathy progression." British Journal of Ophthalmology 103, no. 2 (2018): 222–26. http://dx.doi.org/10.1136/bjophthalmol-2018-311887.

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AimTo analyse retinopathy phenotypes and microaneurysm (MA) turnover in mild non-proliferative diabetic retinopathy (NPDR) as predictors of progression to diabetic central-involved macular oedema (CIMO) in patients with type 2 diabetes mellitus (DM) in two different ethnic populations.Methods 205 patients with type 2 DM and mild NPDR were followed in a prospective observational study for 2 years or until development of CIMO, in two centres from different regions of the world. Ophthalmological examinations, including best-corrected visual acuity (BCVA), fundus photography with RetmarkerDR analy

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Ashraf, Mohamed, Konstantina Sampani, Omar AbdelAl, et al. "Disparity of microaneurysm count between ultrawide field colour imaging and ultrawide field fluorescein angiography in eyes with diabetic retinopathy." British Journal of Ophthalmology 104, no. 12 (2020): 1762–67. http://dx.doi.org/10.1136/bjophthalmol-2019-315807.

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AimsTo compare microaneurysm (MA) counts using ultrawide field colour images (UWF-CI) and ultrawide field fluorescein angiography (UWF-FA).MethodsRetrospective study including patients with type 1 or 2 diabetes mellitus receiving UWF-FA and UWF-CI within 2 weeks. MAs were manually counted in individual Early Treatment Diabetic Retinopathy Study (ETDRS) and extended UWF zones. Fields with MAs ≥20 determined diabetic retinopathy (DR) severity (0 fields=mild, 1–3=moderate, ≥4=severe). UWF-FA and UWF-CI agreement was determined and UWF-CI DR severity sensitivity analysis adjusting for UWF-FA MA co

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Babiuch, Amy S., Charles C. Wykoff, Sari Yordi, et al. "The 2-Year Leakage Index and Quantitative Microaneurysm Results of the RECOVERY Study: Quantitative Ultra-Widefield Findings in Proliferative Diabetic Retinopathy Treated with Intravitreal Aflibercept." Journal of Personalized Medicine 11, no. 11 (2021): 1126. http://dx.doi.org/10.3390/jpm11111126.

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Eyes with proliferative diabetic retinopathy (PDR) have been shown to improve in the leakage index and microaneurysm (MA) count after intravitreal aflibercept (IAI) treatment. The authors investigated these changes via automatic segmentation on ultra-widefield fluorescein angiography (UWFA). Forty subjects with PDR were randomized to receive either 2 mg IAI every 4 weeks (Arm 1) or every 12 weeks (Arm 2) through Year 1. After Year 1, Arm 1 switched to quarterly IAI and Arm 2 to monthly IAI through Year 2. By Year 2, the Arm 1 leakage index decreased by 43% from Baseline (p = 0.03) but increase

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Santos, Ana Rita, Luis Mendes, Maria Helena Madeira, et al. "Microaneurysm Turnover in Mild Non-Proliferative Diabetic Retinopathy is Associated with Progression and Development of Vision-Threatening Complications: A 5-Year Longitudinal Study." Journal of Clinical Medicine 10, no. 10 (2021): 2142. http://dx.doi.org/10.3390/jcm10102142.

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Background: Analysis of retinal microaneurysm turnover (MAT) has been previously shown to contribute to the identification of eyes at risk of developing clinically significant complications associated with diabetic retinopathy (DR). We propose to further characterize MAT as a predictive biomarker of DR progression and development of vision-threatening complications. Methods: 212 individuals with type 2 diabetes (T2D; ETDRS grades 20 and 35) were evaluated annually in a 5-year prospective, longitudinal study, by color fundus photography and optical coherence tomography. Endpoints were diabetic

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Torok, Zsolt, Tunde Peto, Eva Csosz, et al. "Combined Methods for Diabetic Retinopathy Screening, Using Retina Photographs and Tear Fluid Proteomics Biomarkers." Journal of Diabetes Research 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/623619.

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Background. It is estimated that 347 million people suffer from diabetes mellitus (DM), and almost 5 million are blind due to diabetic retinopathy (DR). The progression of DR can be slowed down with early diagnosis and treatment. Therefore our aim was to develop a novel automated method for DR screening.Methods. 52 patients with diabetes mellitus were enrolled into the project. Of all patients, 39 had signs of DR. Digital retina images and tear fluid samples were taken from each eye. The results from the tear fluid proteomics analysis and from digital microaneurysm (MA) detection on fundus ima

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Sędziak-Marcinek, Bogumiła, Sławomir Teper, Elżbieta Chełmecka, et al. "Diabetic Macular Edema Treatment with Bevacizumab Does Not Depend on the Retinal Nonperfusion Presence." Journal of Diabetes Research 2021 (February 26, 2021): 1–15. http://dx.doi.org/10.1155/2021/6620122.

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This study evaluated the relationship between the retinal nonperfusion area (NPA) presence and the effectiveness of bevacizumab treatment (IVB) in patients with diabetic macular edema (DME). It also tested the prognostic usefulness of ultra-wide-field fluorescein angiography (UWFFA) and OptosAdvance software for diabetic retinopathy monitoring. Eighty-nine patients with DME with a macular central subfield thickness CST ≥ 250 μ m , with ( N = 49 eyes) and without ( N = 49 eyes) retinal NPA, underwent nine bevacizumab injections over 12 months. NPA distribution, leakage area distribution, microa

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Hossain, Mubdiul, Aziah Ali, Noramiza Hashim, Wan Noorshahida Mohd Isa, Wan Mimi Diyana Wan Zaki, and Aini Hussain. "Mobile Implementation of Retinal Image Analysis for Efficient Vessel, Optic Disc, and Lesion Detection." JOIV : International Journal on Informatics Visualization 7, no. 3-2 (2023): 1022. http://dx.doi.org/10.30630/joiv.7.3-2.2363.

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Smartphone-based mobile fundus photography is gaining popularity due to the rise of handheld fundus lenses, allowing a portable solution for a mobile-based computer-assisted diagnostic system (CADS). With such a system, professionals can monitor and diagnose numerous retinal diseases, including diabetic retinopathy (DR), glaucoma, age-related macular degeneration, etc. on their smartphone devices. In this study, we proposed a unified CADS tool for smartphone devices that can detect and identify six crucial retinal features utilizing both a filtering approach and a deep learning (DL) approach.

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Sabal, Barbara, Edward Wylęgała, and Sławomir Teper. "Impact of Subthreshold Micropulse Laser on the Vascular Network in Diabetic Macular Edema: An Optical Coherence Tomography Angiography Study." Biomedicines 13, no. 5 (2025): 1194. https://doi.org/10.3390/biomedicines13051194.

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Objectives: To evaluate the short- and long-term effects of subthreshold micropulse laser (SMPL) treatment on the microvascular network in diabetic macular edema (DME). Methods: This 12-month prospective study included 67 eyes (67 patients) with mild DME and good best-corrected visual acuity (BCVA), randomized into SMPL (33 eyes) or sham (34 eyes) groups. Assessments were performed at baseline (T1), 3 months (T2), and 12 months (T3). Optical coherence tomography (OCT) and OCT angiography (OCTA) were used to measure central retinal thickness (CRT), macular thickness (MT), macular volume (MV), f

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Zeng, Qiao-Zhu, Yu-Ou Yao, En-Zhong Jin, Jin-Feng Qu, and Ming-Wei Zhao. "Comparison of 24×20 mm2 swept-source OCTA and fluorescein angiography for the evaluation of lesions in diabetic retinopathy." International Journal of Ophthalmology 15, no. 11 (2022): 1798–805. http://dx.doi.org/10.18240/ijo.2022.11.10.

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AIM: To compare ultra-widefield (24×20 mm2) swept-source optical coherence tomography angiography (SS-OCTA) and fluorescein angiography (FA) in the evaluation of diabetic retinopathy (DR) lesions. METHODS: Forty-six eyes of 23 patients with treatment-naïve DR were included at Peking University People’s Hospital from September 1, 2021, until December 31, 2021, as well as 23 age and gender matched healthy controls. Quantitative assessments of DR lesions on FA and SS-OCTA (superficial capillary plexus, SCP, 24×20 mm2) were performed. RESULTS: Area of fovea avascular zone (FAZ) was larger in DR ca

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Hunt, Magdalena, Sławomir Teper, Adam Wylęgała, and Edward Wylęgała. "Response to 1-Year Fixed-Regimen Bevacizumab Therapy in Treatment-Naïve DME Patients: Assessment by OCT Angiography." Journal of Diabetes Research 2022 (February 21, 2022): 1–12. http://dx.doi.org/10.1155/2022/3547461.

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Purpose. To evaluate the effectiveness of intravitreal bevacizumab treatment in patients with diabetic macular edema (DME) by assessing retinal changes using optical coherence tomography angiography (OCT-A). Methods. This prospective study was performed in patients with treatment-naïve DME. The eyes of patients were imaged using a swept-source OCT system with a scan area of 6 × 6 mm. The DME patients with a central macular thickness (CMT) of ≥300 μm received nine bevacizumab injections within 12 months. The demographic, systemic, and ocular parameters, including the best-corrected visual acuit

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Li, Yu, Meilong Zhu, Guangmin Sun, Jiayang Chen, Xiaorong Zhu, and Jinkui Yang. "Weakly supervised training for eye fundus lesion segmentation in patients with diabetic retinopathy." Mathematical Biosciences and Engineering 19, no. 5 (2022): 5293–311. http://dx.doi.org/10.3934/mbe.2022248.

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<abstract> <sec><title>Objective</title><p>Diabetic retinopathy is the leading cause of vision loss in working-age adults. Early screening and diagnosis can help to facilitate subsequent treatment and prevent vision loss. Deep learning has been applied in various fields of medical identification. However, current deep learning-based lesion segmentation techniques rely on a large amount of pixel-level labeled ground truth data, which limits their performance and application. In this work, we present a weakly supervised deep learning framework for eye fundus lesion

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Hemalakshmi, G. R., and N. B. Prakash. "Detection of Microaneurysms in Fundus Images using ELM Classifier." International Journal of Current Pharmaceutical Review and Research 8, no. 03 (2017). http://dx.doi.org/10.25258/ijcprr.v8i03.9207.

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The main objective of this paper is to detect the microaneurysms which is the sign and symptom for the retinal disease Diabetic Retinopathy (DR). In this work, the input image is preprocessed and then cross sectional scanning is applied for peak detection and property measurement. Feature set from the processed images is extracted and ELM classifier is used for MA detection. The experimental results show the proposed system provides better results compared to existing system.

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Wang, Zhenhua, Xiaokai Li, Mudi Yao, Jing Li, Qing Jiang, and Biao Yan. "A new detection model of microaneurysms based on improved FC-DenseNet." Scientific Reports 12, no. 1 (2022). http://dx.doi.org/10.1038/s41598-021-04750-2.

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AbstractDiabetic retinopathy (DR) is a frequent vascular complication of diabetes mellitus and remains a leading cause of vision loss worldwide. Microaneurysm (MA) is usually the first symptom of DR that leads to blood leakage in the retina. Periodic detection of MAs will facilitate early detection of DR and reduction of vision injury. In this study, we proposed a novel model for the detection of MAs in fluorescein fundus angiography (FFA) images based on the improved FC-DenseNet, MAs-FC-DenseNet. FFA images were pre-processed by the Histogram Stretching and Gaussian Filtering algorithm to imp

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Jayachandran, A., and S. Ganesh. "Deep CNN-based microaneurysm segmentation system in retinal images using multi-level features." Journal of Intelligent & Fuzzy Systems, August 29, 2023, 1–17. http://dx.doi.org/10.3233/jifs-230154.

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Microaneurysms, tiny, circular red dots that occur in retinal fundus images, are one of the earliest symptoms of diabetic retinopathy. Because microaneurysms are small and delicate, detecting them can be difficult. Their small size and cunning character make automatic detection of them difficult. In this study, a novel encoder-decoder network is proposed to segment the MAs automatically and accurately. The encoder part mainly consists of three parts: a low-level feature extraction module composed of a dense connectivity block (Dense Block), a High-resolution Block (HR Block), and an Atrous Spa

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Borrelli, Enrico, Riccardo Sacconi, Maria Brambati, Francesco Bandello, and Giuseppe Querques. "In vivo rotational three-dimensional OCTA analysis of microaneurysms in the human diabetic retina." Scientific Reports 9, no. 1 (2019). http://dx.doi.org/10.1038/s41598-019-53357-1.

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AbstractThe aim of this study was to explore whether rotational three-dimensional (3D) visualization of optical coherence tomography angiography (OCTA) volume data may yield valuable information regarding diabetic retinal microaneurysm (MA) characteristics. In this retrospective, observational study, we collected data from 20 patients (20 eyes) with diabetic retinopathy. Subjects were imaged with the SS-OCTA system (PLEX Elite 9000, Carl Zeiss Meditec Inc., Dublin, CA, USA). The OCTA volume data were processed with a volume projection removal algorithm and then exported to imageJ in order to o

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Ikegami, Yasuko, Tomoyasu Shiraya, Fumiyuki Araki, et al. "Navigated direct photocoagulation with a 30-ms short-pulse laser for treating microaneurysms in diabetic macular edema exhibits a high closure rate." Scientific Reports 13, no. 1 (2023). http://dx.doi.org/10.1038/s41598-023-33260-6.

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AbstractThis study carried out direct photocoagulation for treating microaneurysms (MAs) in diabetic macular edema (DME) using a navigation laser system with a 30-ms pulse duration. The MA closure rate after 3 months was investigated using pre and postoperative fluorescein angiography images. MAs primarily inside the edematous area based on optical coherence tomography (OCT) maps were selected for treatment, and leaking MAs (n = 1151) were analyzed in 11 eyes (eight patients). The total MA closure rate was 90.1% (1034/1151), and the mean MA closure rate in each eye was 86.5 ± 8.4%. Mean centra

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Sakono, Takato, Hiroto Terasaki, Shozo Sonoda, et al. "Comparison of multicolor scanning laser ophthalmoscopy and optical coherence tomography angiography for detection of microaneurysms in diabetic retinopathy." Scientific Reports 11, no. 1 (2021). http://dx.doi.org/10.1038/s41598-021-96371-y.

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AbstractThis study aimed to evaluate the usefulness of multicolor (MC) scanning laser ophthalmoscopy (MC-SLO) in detecting microaneurysm (MA) in eyes with diabetic retinopathy (DR). This was a retrospective cross-sectional study. Eyes with DR underwent fluorescein angiography (FA), MC-SLO, optical coherence tomography angiography (OCTA), and color fundus photography (CFP) were analyzed. The foveal region was cut in an 6 × 6 mm image and the number of MA in each image was counted by retina specialists to determine the sensitivity and positive predictive value. FA results were used as the ground

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"Detection and Classification of Early Stage Lesions in Diabetic Retinopathy using Color Fundus Images." International Journal of Recent Technology and Engineering 8, no. 3 (2019): 4476–80. http://dx.doi.org/10.35940/ijrte.c6806.098319.

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Detection of lesions and classification of Diabetic Retinopathy (DR) play an important role in day-to-day life. In this proposed system, colour fundus image is pre-processed using morphological operations to recover from noises and it is converted into HSV colorspace. Fuzzy C-Means Clustering algorithm (FCMC) is used for segmenting the early stage lesions such as Microaneurysms (Ma), Haemorrhages (HE) and Exudates. Hybrid features such as colour correlogram and speeded up robust features (surf) are extracted to train the classifier. Cascaded Rotation Forest (CRF) classifier is used for classif

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Huber, Kim Lien, Heiko Stino, Thomas Schlegl, et al. "Microaneurysm detection using high‐speed megahertz optical coherence tomography angiography in advanced diabetic retinopathy." Acta Ophthalmologica, December 21, 2023. http://dx.doi.org/10.1111/aos.16619.

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AbstractPurposeTo compare detection rates of microaneurysms (MAs) on high‐speed megahertz optical coherence tomography angiography (MHz‐OCTA), fluorescein angiography (FA) and colour fundus photography (CF) in patients with diabetic retinopathy (DR).MethodsFor this exploratory cross‐sectional study, MHz‐OCTA data were acquired with a swept‐source OCT prototype (A‐scan rate: 1.7 MHz), and FA and CF imaging was performed using Optos® California. MA count was manually evaluated on en face MHz‐OCTA/FA/CF images within an extended ETDRS grid. Detectability of MAs visible on FA images was evaluated

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Vanaja, C. B., and P. Prakasam. "Convolutional block attention gate-based Unet framework for microaneurysm segmentation using retinal fundus images." BMC Medical Imaging 25, no. 1 (2025). https://doi.org/10.1186/s12880-025-01625-0.

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Abstract Background Diabetic retinopathy is a major cause of vision loss worldwide. This emphasizes the need for early identification and treatment to reduce blindness in a significant proportion of individuals. Microaneurysms, extremely small, circular red spots that appear in retinal fundus images, are one of the very first indications of diabetic retinopathy. Due to their small size and weak nature, microaneurysms are tough to identify manually. However, because of the complex background and varied lighting factors, it is challenging to recognize microaneurysms in fundus images automaticall

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Almasi, Ramin, Abbas Vafaei, Elahe Kazeminasab, and Hossein Rabbani. "Automatic detection of microaneurysms in optical coherence tomography images of retina using convolutional neural networks and transfer learning." Scientific Reports 12, no. 1 (2022). http://dx.doi.org/10.1038/s41598-022-18206-8.

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AbstractMicroaneurysms (MAs) are pathognomonic signs that help clinicians to detect diabetic retinopathy (DR) in the early stages. Automatic detection of MA in retinal images is an active area of research due to its application in screening processes for DR which is one of the main reasons of blindness amongst the working-age population. The focus of these works is on the automatic detection of MAs in en face retinal images like fundus color and Fluorescein Angiography (FA). On the other hand, detection of MAs from Optical Coherence Tomography (OCT) images has 2 main advantages: first, OCT is

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