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artificial intelligence and ophthalmology:where does the future lead?

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Annals of Eye Science 2018年第1期 108-109页

作者： Fei Li Xiulan Zhang Zhongshan Ophthalmic Center State Key Laboratory of OphthalmologySun Yat-sen UniversityGuangzhou 510060China

artificial intelligence(AI)is a branch of computer science focusing on designing methods and frameworks that can simulate humans’way of *** area of AI includes robotics,image recognition,language recognition,computer vision,*** learning method is a class of machine learning algorithms that use a cascade of multiple layers of nonlinear processing units for feature extraction and transformation,which grant computers the ability to learn from and make predictions on *** learning networks have been utilized in diagnosis of certain ophthalmic diseases.A recent study by Liu et *** us a very promising algorithm(CC-Cruiser)based on deep convolutional network,achieving excellent diagnostic accuracy of congenital cataract(1).Besides high accuracy of diagnosis,CC-Cruiser also provided doctors with a cloud platform to upload their pictures and get evaluation results.

关键词： diagnosis computer doctor

artificial intelligence and deep learning in ophthalmology:Current status and future perspectives

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Advances in ophthalmology Practice and Research 2022年第3期2卷 47-53页

作者： Kai Jin Juan Ye Department of ophthalmology The Second Affiliated Hospital of Zhejiang University School of MedicineHangzhouChina

Background:The ophthalmology field was among the first to adopt artificial intelligence(AI)in *** availability of digitized ocular images and substantial data have made deep learning(DL)a popular *** text:At the moment,AI in ophthalmology is mostly used to improve disease diagnosis and assist decisionmaking aiming at ophthalmic diseases like diabetic retinopathy(DR),glaucoma,age-related macular degeneration(AMD),cataract and other anterior segment ***,most of the AI systems developed to date are still in the experimental stages,with only a few having achieved clinical *** are a number of reasons for this phenomenon,including security,privacy,poor pervasiveness,trust and explainability ***:This review summarizes AI applications in ophthalmology,highlighting significant clinical considerations for adopting AI techniques and discussing the potential challenges and future directions.

关键词： artificial intelligence Deep learning ophthalmology Diabetic retinopathy Glaucoma Age-related macular degeneration

A quantum-search-based multi-classifier for image recognition

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 21-31页

作者： Lu Liu Xingyu Wu Lufan Zhang Chuan Wang School of artificial intelligence Beijing Normal University Applied Optics Beijing Area Major Laboratory Beijing Normal University

The multi-class classification of images is a pivotal challenge within the realm of image processing. As the volume of visual data continues to expand, there is a burgeoning interest in harnessing the unique capabilities of quantum computation to augment the efficiency of classification tasks. However, many existing methods for training quantum image multi-classifiers parallel classical machine learning techniques, where the requisite circuit measurements increase linearly with the volume of training data. This work introduces a novel approach for training a quantum image multi-classifier based on the quantum search algorithm. We have meticulously conducted rigorous experiments on a handwritten digit dataset, a classic benchmark in the field. The results have been meticulously compared with previous works, and the comparative analysis not only validates the efficiency of our proposed approach, requiring only O(N/b) measurements during training, but also highlights a significant quadratic speedup of the algorithm.

关键词： quantum computation image recognition quantum search algorithm

Multi-Scale Dilated Convolution Network for SPECT-MPI Cardiovascular Disease Classification with Adaptive Denoising and Attenuation Correction

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 299-327页

作者： A.Robert Singh Suganya Athisayamani Gyanendra Prasad Joshi Bhanu Shrestha Department of Computational intelligence SRM Institute of Science and TechnologyKattankulathur603203Tamil NaduIndia School of Computing Sastra Deemed to be UniversityThanjavur613401Tamil NaduIndia Department of artificial intelligence&Software Kangwon National UniversitySamcheok25913Republic of Korea Department of Information Convergence System Graduate School of Smart ConvergenceKwangwoon UniversitySeoul01897Republic of Korea

Myocardial perfusion imaging(MPI),which uses single-photon emission computed tomography(SPECT),is a well-known estimating tool for medical diagnosis,employing the classification of images to show situations in coronary artery disease(CAD).The automatic classification of SPECT images for different techniques has achieved near-optimal accuracy when using convolutional neural networks(CNNs).This paper uses a SPECT classification framework with three steps:1)Image denoising,2)Attenuation correction,and 3)Image *** denoising is done by a U-Net architecture that ensures effective image *** correction is implemented by a convolution neural network model that can remove the attenuation that affects the feature extraction process of ***,a novel multi-scale diluted convolution(MSDC)network is *** merges the features extracted in different scales and makes the model learn the features more *** scales of filters with size 3×3 are used to extract *** three steps are compared with state-of-the-art *** proposed denoising architecture ensures a high-quality image with the highest peak signal-to-noise ratio(PSNR)value of *** proposed classification method is compared with the five different CNN models,and the proposed method ensures better classification with an accuracy of 96%,precision of 87%,sensitivity of 87%,specificity of 89%,and F1-score of 87%.To demonstrate the importance of preprocessing,the classification model was analyzed without denoising and attenuation correction.

关键词： SPECT-MPI CAD MSDC denoising attenuation correction classification

Characterization of ultraviolet communication in a mixed aerosol environment

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Optoelectronics Letters 2025年第2期 77-84页

作者： ZHAO Taifei SUN Yuxin WANG Wuxin ZHANG Haijun PAN Feixiang WU Hao artificial intelligence Key Laboratory of Sichuan Province Sichuan University of Science & Engineering Faculty of Automation and Information Engineering Xi'an University of Technology

Wireless ultraviolet (UV) has strong scattering characteristics and can communicate through non-direct *** UV signals are transmitted in the atmosphere,they are affected by the absorption and scattering effects of atmospheric particles and atmospheric turbulence,resulting in attenuation of UV signal energy and reduced reliability of the communication *** paper focuses on the channel model of UV non-direct-view single scattering communication,and simulates and analyzes the communication characteristics of UV light in atmospheric turbulence and mixed aerosol environment under horizontal,vertical and oblique range communication *** results show that at equal relative humidity,the wireless UV non-directive scattering communication performance for vertical communication scenarios is more affected by the mixed aerosol environment and the communication performance is worse.

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Event-Triggered Robust Parallel Optimal Consensus Control for Multiagent Systems

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IEEE/CAA Journal of Automatica Sinica 2025年第1期 40-53页

作者： Qinglai Wei Shanshan Jiao Qi Dong Fei-Yue Wang IEEE the Institute of Systems Engineering Macau University of Science and Technology the State Key Laboratory of Multimodal artificial intelligence Systems Institute of Automation Chinese Academy of Sciences the School of artificial intelligence University of Chinese Academy of Sciences China Academy of Electronics and Information Technology the State Key Laboratory of Multimodal artificial intelligence Systems the School of artificial intelligence University of Chinese Academy of Sciences

This paper highlights the utilization of parallel control and adaptive dynamic programming(ADP) for event-triggered robust parallel optimal consensus control(ETRPOC) of uncertain nonlinear continuous-time multiagent systems(MASs).First, the parallel control system, which consists of a virtual control variable and a specific auxiliary variable obtained from the coupled Hamiltonian, allows general systems to be transformed into affine systems. Of interest is the fact that the parallel control technique's introduction provides an unprecedented perspective on eliminating the negative effects of disturbance. Then, an eventtriggered mechanism is adopted to save communication resources while ensuring the system's stability. The coupled HamiltonJacobi(HJ) equation's solution is approximated using a critic neural network(NN), whose weights are updated in response to events. Furthermore, theoretical analysis reveals that the weight estimation error is uniformly ultimately bounded(UUB). Finally,numerical simulations demonstrate the effectiveness of the developed ETRPOC method.

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Preface: Water-related vision

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Science China Technological Sciences 2025年第1期 5页

作者： Zhe SUN Xuelong LI School of artificial intelligence Optics and Electronics (iOPEN)Northwestern Polytechnical University Key Laboratory of Intelligent Interaction and Applications (Northwestern Polytechnical University) Ministry of Industry and Information Technology The Institute of artificial intelligence (TeleAI) China Telecom

Water-related optical imaging serves as a crucial tool and method for human beings to understand aquatic environments,develop and utilize water resources, and protect aquatic ecosystems. It offers distinct advantages such as intuitive target detection, high imaging resolution, and rich information content. However, due to the absorption and scattering properties of water, water-related optical imaging is often plagued by noise, making the acquisition of clear images a challenging task.

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Science China Technological Sciences 2025年第1期 6-53页

Water-related optical imaging constitutes a pivotal domain within the field of water-related optics and vision,furnishing essential tools for comprehending the water-related environment, harnessing water resources, and safeguarding water ecology. Its merits encompass facile target detection, elevated imaging resolution, and copious information ***, the formidable challenge of attaining clear images in water-related environments is challenging due to the water's absorption and scattering properties. Substantial strides have been achieved in recent years through advancements in software and hardware optical imaging and processing techniques. This review offers a comprehensive exploration of the present state of water-related optical imaging, spanning historical, theoretical, and methodological dimensions. A retrospective analysis of the historical evolution of water-related optical imaging is presented, accompanied by a detailed exposition of the operational principles and the latest noteworthy advancements in various categories of water-related optical imaging. Furthermore, a meticulous comparative analysis of these methodologies is undertaken. These approaches not only enhance water-related optical imaging efficacy but also furnish robust support for scientific inquiry and resource exploitation in water-related environments. This review enhances the comprehension of advancements in water-related optical imaging research, acting as a crucial touchpoint for future explorations and innovations. Water-related optical imaging is critical for comprehending marine ecosystems, supporting environmental conservation, and improving industry efficiency.

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A Novel Self-Supervised Learning Network for Binocular Disparity Estimation

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 209-229页

作者： Jiawei Tian Yu Zhou Xiaobing Chen Salman A.AlQahtani Hongrong Chen Bo Yang Siyu Lu Wenfeng Zheng Department of Computer Science and Engineering Major in Bio Artificial IntelligenceHanyang UniversityAnsan-si15577Republic of Korea School of Electrical and Computer Engineering Louisiana State UniversityBaton RougeLA 70803USA Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11574Saudi Arabia School of Automation University of Electronic Science and Technology of ChinaChengdu610054China

Two-dimensional endoscopic images are susceptible to interferences such as specular reflections and monotonous texture illumination,hindering accurate three-dimensional lesion reconstruction by surgical *** study proposes a novel end-to-end disparity estimation model to address these *** approach combines a Pseudo-Siamese neural network architecture with pyramid dilated convolutions,integrating multi-scale image information to enhance robustness against lighting *** study introduces a Pseudo-Siamese structure-based disparity regression model that simplifies left-right image comparison,improving accuracy and *** model was evaluated using a dataset of stereo endoscopic videos captured by the Da Vinci surgical robot,comprising simulated silicone heart sequences and real heart video *** results demonstrate significant improvement in the network’s resistance to lighting interference without substantially increasing ***,the model exhibited faster convergence during training,contributing to overall performance *** study advances endoscopic image processing accuracy and has potential implications for surgical robot applications in complex environments.

关键词： Parallax estimation parallax regression model self-supervised learning Pseudo-Siamese neural network pyramid dilated convolution binocular disparity estimation