Segmentation of Diabetic Retinopathy Lesions in Retinal Fundus Images Using Multi-View Convolutional Neural Networks

Khastavaneh, Hassan; Ebrahimpour-Komleh, Hossein

doi:10.5812/iranjradiol.99148

Cited by 4 publications

(3 citation statements)

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“…Computational and Mathematical Methods in Medicine China's e-commerce information platform started relatively late, has no rich experience, and has many problems. First of all, the sharing and transmission of e-commerce information is separated from reality, mainly because the actual operation process of e-commerce is not fully considered in the design process of the information platform architecture [19,20]. The second is the lack of value-added services, resulting in the current Chinese e-commerce information platform unable to adapt to the development needs of the IOT technology.…”

Section: Introductionmentioning

confidence: 99%

The Development Relationship between Cross-Border e-Commerce and Internet of Things Technology Coupling in Digital Economy Based on Neural Network Model

Liu¹

2022

Computational and Mathematical Methods in Medicine

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Compared with the traditional trading model, the problem of information asymmetry in export cross-border e-commerce (CBEC) transactions actually exists. Since the buyers and sellers of export CBEC are located in different countries, it is difficult for both parties to make accurate judgments on each other’s credit. Besides, the number of export CBEC financing is relatively small, and the financing situation is not optimistic. Fortunately, the Internet of Things (IOT) technology has a wide range of applications and strong social penetration, especially in e-commerce, which can effectively improve payment, logistics, and distribution. By employing the concept of the IOT, this paper expounds the application of the IOT in the e-commerce transaction process and the impact of the IOT on the development of e-commerce. Besides, this paper also proposes some security issues in the application of the IOT in e-commerce. In addition, this paper analyzes the relationship and development trend of CBEC and IOT technology; meanwhile, it also points out the practical problems currently faced by combining the regional advantage of a certain region. The e-commerce industry develops IOT technology and drives innovation-driven development in the region. In addition, this paper builds an evaluation index system for the development of export CBEC enterprises based on the analysis of the problems and reasons by using the sample data to train the BP neural network and using the test samples to test the model. It is found that the model accuracy rate is 89.47%. Then, this paper also takes the export CBEC company A as an example to conduct empirical research and to prove the operability of the credit evaluation model. Finally, it provides relevant suggestions for improving the credit evaluation system of export CBEC enterprises.

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Section: Introductionmentioning

confidence: 99%

The Development Relationship between Cross-Border e-Commerce and Internet of Things Technology Coupling in Digital Economy Based on Neural Network Model

Liu¹

2022

Computational and Mathematical Methods in Medicine

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“…erefore, the current-carrying capacity of high-temperature superconducting tapes plays an extremely important role in the design, economic performance, and operational stability of high-temperature superconducting electrical devices. e study of the electromagnetic properties of the superconducting electrical device must be based on the anisotropy of the critical current and magnetic field of the high-temperature superconducting tape, and the analysis of the magnetic field distribution of the high-temperature superconducting electrical device is the basis for the analysis and design of the electromagnetic properties of the high-temperature superconducting electrical device [18,19].…”

Section: Introductionmentioning

confidence: 99%

Electromagnetic Field Analysis and Optimization Method of High-Temperature Superconducting Transformer under the Influence of Abnormal Voltage

Zhi

Zhang

Yang

2022

Mobile Information Systems

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High-temperature superconducting transformers are an important research topic of superconducting technology in power applications, and electromagnetic field analysis and optimization are the basis for the design and application of high-temperature superconducting transformers. The electromagnetic field analysis of high-temperature superconducting transformers should consider the superconducting properties of the materials, that is, the properties of critical current and magnetic field. This paper aims to study the electromagnetic field analysis and optimization method of high-temperature superconducting transformer under the influence of abnormal voltage. Due to the energy loss of high-temperature superconducting transformers, in order to study the economy and reliability of high-temperature superconducting transformers, in this paper, the core loss, winding AC loss, and coil power consumption of high-temperature superconducting transformers are analyzed under normal operation and short-circuit fault conditions, respectively. The power and stress on the windings are analyzed. In order to take into account the current-carrying capacity, short-circuit loss, and short-circuit electromotive force of superconducting windings in normal operation, a concentrically placed double-cake coil structure is selected in this paper, and according to different optimization objectives, a global optimization method is used to evaluate the structure of the coil. The structural parameters of the high-temperature superconducting transformer are optimized, including the structural parameters of the magnetic conducting ring. It is found that that abnormal voltage will affect the electromagnetic field of high-temperature superconducting transformers, including winding circulating current, leakage magnetic field, and current distribution.

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“…Therefore, researchers at home and abroad have devoted themselves to the research of DR classification with great enthusiasm and developed a variety of classification and diagnosis methods. However, when the severity of the disease is different, there is not much difference between the DR images, and the feature extraction and classification work are difficult to perform well [19].…”

Section: Introductionmentioning

confidence: 99%

Analysis and Recognition of Clinical Features of Diabetes Based on Convolutional Neural Network

Wang

Ping

Yang

2022

Computational and Mathematical Methods in Medicine

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Diabetes mellitus is a common chronic noncommunicable disease, the main manifestation of which is the long-term high blood sugar level in patients due to metabolic disorders. However, due to excessive reliance on the clinical experience of ophthalmologists, our diagnosis takes a long time, and it is prone to missed diagnosis and misdiagnosis. In recent years, with the development of deep learning, its application in the auxiliary diagnosis of diabetic retinopathy has become possible. How to use the powerful feature extraction ability of deep learning algorithm to realize the mining of massive medical data is of great significance. Therefore, under the action of computer-aided technology, this paper processes and analyzes the retinal images of the fundus through traditional image processing and convolutional neural network-related methods, so as to achieve the role of assisting clinical treatment. Based on the admission records of diabetic patients after data analysis and feature processing, this paper uses an improved convolutional neural network algorithm to establish a model for predicting changes in diabetic conditions. The model can assist doctors to judge the patient’s treatment effect by using it based on the case records of inpatient diagnosis and treatment and to predict the risk of readmission of inpatients after discharge. It also can help to judge the effectiveness of the treatment plan. The results of the study show that the model proposed in this paper has a lower probability of misjudging patients with poor recovery as good recovery, and the prediction is more accurate.

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Segmentation of Diabetic Retinopathy Lesions in Retinal Fundus Images Using Multi-View Convolutional Neural Networks

Abstract: Figure 1. ROC curves for fully trained and fine tuned DenseNet Conclusion: The results showed the superiority of the transfer learning approach in tumor classification. Higher statistical metrics with lower training time makes this approach more compatible with SWE images.

Cited by 4 publications

References 0 publications

The Development Relationship between Cross-Border e-Commerce and Internet of Things Technology Coupling in Digital Economy Based on Neural Network Model

The Development Relationship between Cross-Border e-Commerce and Internet of Things Technology Coupling in Digital Economy Based on Neural Network Model

Electromagnetic Field Analysis and Optimization Method of High-Temperature Superconducting Transformer under the Influence of Abnormal Voltage

Analysis and Recognition of Clinical Features of Diabetes Based on Convolutional Neural Network

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