Kanupriya Mittal^*, V. Mary Anita Rajam

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1907-1921, 2023, DOI:10.32604/iasc.2023.029037

Abstract An automated retinal disease detection system has long been in existence and it provides a safe, no-contact and cost-effective solution for detecting this disease. This paper presents a game theory-based dynamic weighted ensemble of a feature extraction-based machine learning model and a deep transfer learning model for automatic retinal disease detection. The feature extraction-based machine learning model uses Gaussian kernel-based fuzzy rough sets for reduction of features, and XGBoost classifier for the classification. The transfer learning model uses VGG16 or ResNet50 or Inception-ResNet-v2. A novel ensemble classifier based on the game theory approach is proposed for the fusion of the… More >

Huan Ma¹, Cong Nie¹, Ying Chen, Jinmiao Li, Yanjie Xie, Zhixin Tang, Yang Gao, Siming Ai, Yuxiang Mao, Qian Sun, Rong Lu

Oncology Research, Vol.28, No.7-8, pp. 745-761, 2020, DOI:10.3727/096504021X16130322409507

Abstract Cell cycle deregulation is involved in the pathogenesis of many cancers and is often associated with protein kinase aberrations, including the polo-like kinase 1 (PLK1). We used retinoblastoma, an intraocular malignancy that lacks targeted therapy, as a disease model and set out to reveal targetability of PLK1 with a small molecular inhibitor ON-01910.Na. First, transcriptomic analysis on patient retinoblastoma tissues suggested that cell cycle progression was deregulated and confirmed that PLK1 pathway was upregulated. Next, antitumor activity of ON-01910.Na was investigated in both cellular and animal levels. Cytotoxicity induced by ON-01910.Na was tumor specific and dose dependent in retinoblastoma cells,… More >

Ghassan Ahmed Ali¹, Thamer Mitib Ahmad Al Sariera^2,*, Muhammad Akram¹, Adel Sulaiman¹, Fekry Olayah¹

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1601-1616, 2023, DOI:10.32604/csse.2023.026119

Abstract Damage of the blood vessels in retina due to diabetes is called diabetic retinopathy (DR). Hemorrhages is the first clinically visible symptoms of DR. This paper presents a new technique to extract and classify the hemorrhages in fundus images. The normal objects such as blood vessels, fovea and optic disc inside retinal images are masked to distinguish them from hemorrhages. For masking blood vessels, thresholding that separates blood vessels and background intensity followed by a new filter to extract the border of vessels based on orientations of vessels are used. For masking optic disc, the image is divided into sub-images… More >

M. P. Karthikeyan^1,*, E. A. Mary Anita²

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 567-580, 2023, DOI:10.32604/iasc.2023.026243

Abstract In recent years, there has been a significant increase in the number of people suffering from eye illnesses, which should be treated as soon as possible in order to avoid blindness. Retinal Fundus images are employed for this purpose, as well as for analysing eye abnormalities and diagnosing eye illnesses. Exudates can be recognised as bright lesions in fundus pictures, which can be the first indicator of diabetic retinopathy. With that in mind, the purpose of this work is to create an Integrated Model for Exudate and Diabetic Retinopathy Diagnosis (IM-EDRD) with multi-level classifications. The model uses Support Vector Machine… More >

Syed Irtaza Haider¹, Khursheed Aurangzeb^2,*, Musaed Alhussein²

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1501-1526, 2022, DOI:10.32604/cmc.2022.025479

Abstract The accurate segmentation of retinal vessels is a challenging task due to the presence of various pathologies as well as the low-contrast of thin vessels and non-uniform illumination. In recent years, encoder-decoder networks have achieved outstanding performance in retinal vessel segmentation at the cost of high computational complexity. To address the aforementioned challenges and to reduce the computational complexity, we propose a lightweight convolutional neural network (CNN)-based encoder-decoder deep learning model for accurate retinal vessels segmentation. The proposed deep learning model consists of encoder-decoder architecture along with bottleneck layers that consist of depth-wise squeezing, followed by full-convolution, and finally depth-wise… More >

A. Geetha, N. B. Prakash^*

Computer Systems Science and Engineering, Vol.43, No.3, pp. 1041-1055, 2022, DOI:10.32604/csse.2022.023680

Abstract Today, many eye diseases jeopardize our everyday lives, such as Diabetic Retinopathy (DR), Age-related Macular Degeneration (AMD), and Glaucoma. Glaucoma is an incurable and unavoidable eye disease that damages the vision of optic nerves and quality of life. Classification of Glaucoma has been an active field of research for the past ten years. Several approaches for Glaucoma classification are established, beginning with conventional segmentation methods and feature-extraction to deep-learning techniques such as Convolution Neural Networks (CNN). In contrast, CNN classifies the input images directly using tuned parameters of convolution and pooling layers by extracting features. But, the volume of training… More >

Qaisar Abbas^1,*, Mostafa E. A. Ibrahim^1,2, Abdul Rauf Baig¹

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4573-4590, 2022, DOI:10.32604/cmc.2022.023670

Abstract Diabetic retinopathy (DR) diagnosis through digital fundus images requires clinical experts to recognize the presence and importance of many intricate features. This task is very difficult for ophthalmologists and time-consuming. Therefore, many computer-aided diagnosis (CAD) systems were developed to automate this screening process of DR. In this paper, a CAD-DR system is proposed based on preprocessing and a pre-train transfer learning-based convolutional neural network (PCNN) to recognize the five stages of DR through retinal fundus images. To develop this CAD-DR system, a preprocessing step is performed in a perceptual-oriented color space to enhance the DR-related lesions and then a standard… More >

Sonali Dash¹, Sahil Verma^2,*, Kavita², N. Z. Jhanjhi³, Mehedi Masud⁴, Mohammed Baz⁵

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2459-2476, 2022, DOI:10.32604/cmc.2022.020904

Abstract Segmentation of vessel in retinal fundus images is a primary step for the clinical identification for specific eye diseases. Effective diagnosis of vascular pathologies from angiographic images is thus a vital aspect and generally depends on segmentation of vascular structure. Although various approaches for retinal vessel segmentation are extensively utilized, however, the responses are lower at vessel's edges. The curvelet transform signifies edges better than wavelets, and hence convenient for multiscale edge enhancement. The bilateral filter is a nonlinear filter that is capable of providing effective smoothing while preserving strong edges. Fast bilateral filter is an advanced version of bilateral… More >

Shumukh M. Aljuaid^*, Arshiya S. Ansari

Computer Systems Science and Engineering, Vol.41, No.3, pp. 1009-1025, 2022, DOI:10.32604/csse.2022.020785

Abstract This paper presents a novel method of a secured card-less Automated Teller Machine (ATM) authentication based on the three bio-metrics measures. It would help in the identification and authorization of individuals and would provide robust security enhancement. Moreover, it would assist in providing identification in ways that cannot be impersonated. To the best of our knowledge, this method of Biometric_ fusion way is the first ATM security algorithm that utilizes a fusion of three biometric features of an individual such as Fingerprint, Face, and Retina simultaneously for recognition and authentication. These biometric images have been collected as input data for… More >

JIUCHUN GUO¹, JIE PAN^2,*, QIANQIAN GUO²

BIOCELL, Vol.46, No.2, pp. 505-510, 2022, DOI:10.32604/biocell.2021.015785

Abstract The excessive energy of light, especially the invisible rays with lower wavelength, is basically absorbed by retinal pigment epithelium (RPE) and usually causes DNA damage. The molecular mechanism behind DNA damage repair response to this frequent stress in RPE is not clearly understood. In this study, we determined that the Fanconi anemia (FA) pathway was activated in human RPE ARPE-19 cells after ultraviolet (UV) B and C treatment. Moreover, immunoprecipitation (IP) of FANCD2 indicated that denticleless E3 ubiquitin protein ligase homolog (DTL) closely interacted with FANCD2. Knockdown of DTL weakened the activity of the FA pathway in ARPE-19 cells responding… More >