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Application of graph-curvature features in computer-aided diagnosis for histopathological image identification of gastric cancer

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Intelligent Medicine 2024年第3期4卷 141-152页

作者： Ruilin He Chen Li Xinyi Yang Jinzhu Yang Tao Jiang Marcin Grzegorzek Hongzan Sun Microscopic Image and Medical Image Analysis Group College of Medicine and Biological Information EngineeringNortheastern UniversityShenyangLiaoning 110016China Key Laboratory of Intelligent Computing in Medical Image Ministry of EducationNortheastern UniversityShenyangLiaoning 110016China School of Intelligent Medicine Chengdu University of Traditional Chinese MedicineChengduSichuan 610075China International Joint Institute of Robotics and Intelligent Systems Chengdu University of Information TechnologyChengduSichuan 610225China Institute for Medical Informatics University of LuebeckLuebeckGermany Department of Knowledge Engineering University of Economics in KatowiceKatowicePoland Shengjing Hospital of China Medical University ShenyangLiaoning 110136China

Background Histopathology diagnosis is often regarded as the final diagnostic method for malignant tumors;however,it has some *** study explored a computer-aided diagnostic method that can be used to identify benign and malignant gastric cancer using histopathological *** The most suitable process was selected through multiple experiments by comparing multiple meth-ods and features for ***,the U-net was applied to segment the ***,the nucleus was extracted from the segmented image,and the minimum spanning tree(MST)diagram structure that can cap-ture the topological information was *** third step was to extract the graph-curvature features of the histopathological image according to the MST ***,by inputting the graph-curvature features into the classifier,the recognition results for benign or malignant cancer can be *** During the experiment,we used various methods for *** the image segmentation stage,U-net,watershed algorithm,and Otsu threshold segmentation methods were *** found that the U-net method,combined with multiple indicators,was the most suitable for segmentation of histopathological *** the feature extraction stage,in addition to extracting graph-edge and graph-curvature features,several basic im-age features were extracted,including the red,green and blue feature,gray-level co-occurrence matrix feature,histogram of oriented gradient feature,and local binary pattern *** the classifier design stage,we exper-imented with various methods,such as support vector machine(SVM),random forest,artificial neural network,K nearest neighbors,VGG-16,and *** comparison and analysis,it was found that classifica-tion results with an accuracy of 98.57%can be obtained by inputting the graph-curvature feature into the SVM classifier.

关键词： Gastric cancer Graph-curvature feature Image identification

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Deep Learning-Based Leaf Image Analysis for Tomato Plant Disease Detection and Classification

Deep Learning-Based Leaf Image Analysis for Tomato Plant Dis...

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IEEE International Conference on Image Processing

作者： Ammar Chouchane Abdelmalik Ouamanea El Ouanas Belabbaci Yassine Himeur Abbes Amira University Center of Barika Amdoukal Road Barika Algeria Laboratory of LI3C University of Biskra Biskra Algeria Laboratory of Medical Informatics (LIMED) Faculty of Technology University of Bejaia Bejaia Algeria College of Engineering and Information Technology University of Dubai Dubai UAE Department of Computer Science University of Sharjah UAE

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

Tomato plant disease detection and classification, utilizing leaf images through deep learning, intersects the fields of plant pathology and agriculture. Deep learning has demonstrated significant potential in accurately identifying and classifying various plant diseases from leaf images. In this study, we introduce a hybrid system that combines a potent machine learning algorithm, Exponential Discriminant Analysis (EDA), with a transfer learning process leveraging recent and advanced deep networks, including ResNet50, Darknet53, DenseNet201, and EfficientNetB0. This system was evaluated using two challenging datasets: Taiwan and PlantVillage tomato leaf datasets. The experimental results underscore the high competitiveness of the proposed method, achieving mean accuracies of 98.29% and $\mathbf{9 8. 0 9 \%}$ on these datasets, respectively.

关键词： Deep learning Plant diseases Pathology Machine learning algorithms Image analysis Accuracy Plants (biology)

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Intrinsic Cramér-Rao Bound based 6D Localization and Tracking for 5G/6G Systems

arXiv

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arXiv 2025年

作者： Xu, Xueting Chen, Hui Shen, Shengqiang Kim, Hyowon Fang, Xu Peng, Ao Jiang, Fan Wymeersch, Henk Department of Broadband Communications Pengcheng Laboratory Shenzhen518055 China Department of Electrical Engineering Chalmers University of Technology Gothenburg412 58 Sweden School of Information and Control Engineering China University of Mining and Technology Xuzhou221000 China Department of Electronics Engineering Chungnam National University Daejeon34134 Korea Republic of School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore School of Informatics Xiamen University Fujian Xiamen361005 China

Localization and tracking are critical components of integrated sensing and communication (ISAC) systems, enhancing resource management, beamforming accuracy, and overall system reliability through precise *** to the high path loss of the high-frequency systems, antenna arrays are required at the transmitter and receiver sides for beamforming gain. However, beam misalignment may occur, which requires accurate tracking of the six-dimensional (6D) state, namely, 3D position and 3D orientation. In this work, we first address the challenge that the rotation matrix, being part of the Lie group rather than Euclidean space, necessitates the derivation of the ICRB for an intrinsic performance benchmark. Then, leveraging the derived ICRB, we develop two filters-one utilizing pose fusion and the other employing error-state Kalman filter to estimate the UE’s 6D state for different computational resource consumption and accuracy requirements. Simulation results validate the ICRB and assess the performance of the proposed filters, demonstrating their effectiveness and improved accuracy in 6D state tracking. © 2025, CC BY.

关键词： Cramer-Rao bounds

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Development of a Method to Determine the Environmental Burden of Diseases and an Application to Identify Factors Driving Changes in the Number of PM_(2.5)-Related Deaths in China between 2000 and 2010

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Environment & Health 2024年第9期2卷 642-650页

作者： Ning Kang Pengfei Li Tao Xue Tong Zhu Institute of Reproductive and Child Health National Health Commission Key Laboratory of Reproductive Health/Department of Epidemiology and BiostatisticsMinistry of Education Key Laboratory of Epidemiology of Major Diseases(PKU)School of Public HealthPeking University Health Science CenterBeijing 100191China Institute of Medical Technology Peking University Health Science CenterBeijing 100191China Advanced Institute of Information Technology Peking UniversityHangzhou 311215China State Environmental Protection Key Laboratory of Atmospheric Exposure and Health Risk Management and Center for Environment and HealthPeking UniversityBeijing 100871China State Environmental Protection Key Laboratory of Atmospheric Exposure and Health Risk Management and Center for Environment and Health and State Key Joint Laboratory of Environment Simulation and Pollution ControlCollege of Environmental Sciences and EngineeringPeking UniversityBeijing 100871China

The attributable burden is codetermined by the exposure level and nontarget ***,the conventional method of health impact assessment based on preestablished exposure−response functions includes only a few well-known characteristics and thus is insufficient to capture the comprehensive *** aimed to develop a method to fuse health impact assessment with epidemiological analysis and to identify factors driving baseline *** method was applied to identify the factors underlying the change in the number of fine particulate matter(PM_(2.5))related deaths in China between 2000 and *** the study period,the number of PM_(2.5)-related deaths across China's Mainland increased by 0.62(95%CI:0.57,0.69)million,with 0.65(95%CI:0.47,0.91)million,0.55(95%CI:0.39,0.79)million,and 0.11(95%CI:0.06,0.18)million deaths being associated with increased PM_(2.5)exposure,population aging,and growth in population size,***,economic growth,urbanization,improvement of welfare services,and improvement of hospital services resulted in 0.25(95%CI:0.15,0.40)million,0.16(95%CI:0.10,0.27)million,0.16(95%CI:0.09,0.26)million,and 0.09(95%CI:0.05,0.15)million fewer deaths,*** indicated that increased exposure was the major driver of the change in the number of PM_(2.5)-related deaths,and economic growth was the main driver of increased resilience to air pollution.

关键词： health burden decomposition analysis air pollution fine particulate matter premature deaths

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Mechanism of defect evolution in H^(+)and He^(+)implanted InP

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Chinese Physics B 2021年第8期30卷 70-74页

作者： Ren-Jie Liu Jia-Jie Lin N Daghbouj Jia-Liang Sun Tian-Gui You Peng Gao Nie-Feng Sun Min Liao Key Laboratory of Low Dimensional Materials and Application Technology of Ministry of Education School of Materials Science and EngineeringXiangtan UniversityXiangtan 411105China Hunan Provincial Key Laboratory of Thin Film Materials and Devices School of Materials Science and EngineeringXiangtan UniversityXiangtan 411105China State Key Laboratory of Functional Materials for Informatics Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghai 200050China China Nanhu Academy of Electronics and Information Technology Jiaxing 314000China Department of Control Engineering Faculty of Electrical EngineeringCzech Technical University in PragueTechnick´a 216000 Prague 6Czechia Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China Science and Technology on Power Sources Laboratory Tianjin Institute of Power SourcesTianjin 300384China The 13th Research Institute CETCShijiazhuang 050051China

The defect evolution in InP with the 75 keV H^(+)and 115 keV He^(+)implantation at room temperature after subsequent annealing has been investigated in *** the same ion implantation fluence,the He^(+)implantation caused much broader damage distribution accompanied by much higher out-of-plane strain with respect to the H^(+)implanted *** annealing,the H^(+)implanted InP did not show any blistering or exfoliation on the surface even at the high fluence and the H2 molecules were stored in the heterogeneously oriented platelet ***,the He molecules were stored into the large bubbles which relaxed toward the free surface,creating blisters at the high fluence.

关键词： ion implantation defect evolution ion-slicing damaged band

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Middle East and North African Health informatics Association (MENAHIA): Technological initiatives for 'One Health'

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Yearbook of medical informatics 2023年第1期32卷 320-329页

作者： Abd-Alrazaq, Alaa Al-Shorbaji, Najeeb Lakhdari, Kheira Elbokl, Ahmed Farouk, Hani Wahba, Hoda Elgasser, Naema Mohell, Rania Emara, Tamer Ayatollahi, Haleh Kalhori, Sharareh R. Niakan Rabiei, Reza Tara, Mahmood Akhu-Zaheya, Laila Al-Qutob, Raeda Alrazak, Sadam Alabed Al-Jafar, Eiman Alhuwail, Dari Ghazal, Hassan Dehbi, Zineb El Otmani Al Idrissi, Najib Fihri, Ouafaa Fassi Belyamani, Lahcen Shahzad, Tariq Ahmed, Zakiuddin Ahmad, Arfan Shah, Zubair Hamra, Eman Abu Taweel, Adel Nashwan, Abdulqadir J. Househ, Mowafa Hamdi, Mounir Al-Thani, Dena Alam, Tanvir Alshammari, Abdulwahhab Alnafrani, Sana Alali, Haitham AI Center for Precision Health Weill Cornell Medicine-Qatarc Doha Qatar EHealth Development Association Amman Jordan Abou Bekr Belkaid University of Tlemcen Chetouane Algeria Ain Shams University Virtual Hospital Ain Shams University Cairo Egypt Ain Shams University Cairo Egypt World Health Organization Cairo Egypt Alexandria Regional Blood Transfusion Center Alexandria University Alexandria Egypt Health Management and Economics Research Center Health Management Research Institute Iran University of Medical Sciences Tehran Iran Department of Health Information Management School of Health Management and Information Sciences Iran University of Medical Sciences Tehran Iran Department of Health Information Management School of Allied Medical Sciences Tehran University of Medical Sciences Tehran Iran Peter L. Reichertz Institute for Medical Informatics (PLRI) Technical University of Braunschweig Hannover Medical School Braunschweig Germany Department of Health Information Technology and Management School of Allied Medical Sciences Shahid Beheshti University of Medical Sciencesc Tehran Iran Department of Medical Informatics Faculty of Medicine Mashhad University of Medical Sciencesc Mashhad Iran School of Nursing Jordan University of Science and Technology Jordan Jordan Centre for Disease Control and Prevention Amman Jordan Faculty of Applied Science and Engineering University of Toronto Toronto Canada Kuwait Health Informatics Association Kuwait Information Science Department College of Life Sciences Kuwait University Kuwait Health Informatics Unit Dasman Diabetes Institute Kuwait Mohammed VI University of Health Sciences Casablanca Morocco National Center for Scientific and Technical Research (CNRST) Rabat Morocco Hassan II Agronomic and Veterinary Institute Rabat Morocco COMSATS University Islamabad Sahiwal Campus Islamabad Pakistan Digital Care Karachi Pakistan College of Science and Engineering Hamad Bin Khalifa University Doha Qatar Al Quds Unive

MENAHIA (Middle East and North African Health informatics Association) is the International medical informatics Association chapter dedicated to the Middle East and North Africa region. This region is rapidly growing in terms of the use of health informatics or what has been recently coined digital health. Human health is highly affected by the health of the environment, animal health, food, nutrition, climate change, and many other factors that are beyond the biological or genetic structure of human beings. The impact of animal health and the health of the environment on people's health is an old phenomenon but recent reemerging and appearance of diseases have clearly demonstrated the link between these. The Novel Coronavirus disease (COVID-19) that almost all of us have been suffering from is an example of this. A number of countries in the region have already shown the depth and the work that they do to integrate the concept of 'One Health' in the public health surveillance system as they have described the work that has been done to capture data from databases other than those dealing with human beings. The examples that were provided to monitor the health of animals, agriculture, environmental health, climate change, and man-made and natural disasters are just examples of what countries have been registering in their databases and informing the health authorities of these changes and emerging trends. © The Author(s) 2023.

关键词： 'One Health' 'One Health' informatics Algeria Artificial Intelligence Climate Change Digital Health Egypt Health informatics Health information Technologies International medical informatics Association (IMIA) Iran Jordan Kuwait MENAHIA Middle East and North Africa Morocco Pakistan Palestine Qatar Saudi Arabia United Arab Emirates Zoonitic Diseases

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Key considerations on the development of biodegradable biomaterials for clinical translation of medical devices:With cartilage repair products as an example

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Bioactive Materials 2022年第3期7卷 332-342页

作者： Li Wang Xiaolei Guo Jiaqing Chen Zhen Zhen Bin Cao Wenqian Wan Yuandong Dou Haobo Pan Feng Xu Zepu Zhang Jianmei Wang Daisong Li Quanyi Guo Qing Jiang Yanan Du Jiakuo Yu Boon Chin Heng Qianqian Han Zigang Ge Department of Biomedical Engineering College of EngineeringPeking UniversityBeijingPR China Center for Medical Device Evaluation National Medical Products AdministrationBeijingPR China Jiangsu DissueTech Medical Technology Co.Ltd|DeJian Group SuzhouPR China State Key Laboratory of High Performance Ceramics and Superfine Microstructure Shanghai Institute of CeramicsChinese Academy of SciencesShanghaiPR China Research Center for Human Tissue and Organs Degeneration Shenzhen Institute of Advanced TechnologyChinese Academy of ScienceShenzhenPR China Bioinspired Engineering and Biomechanics Center(BEBC) MOE Key Laboratory of Biomedical Information EngineeringSchool of Life Science and TechnologyXi’an Jiaotong UniversityXi’anPR China Beijing Institute of Science and Technology Evaluation BeijingPR China Institute of Orthopedics Chinese PLA General HospitalBeijingPR China Department of Sports Medicine and Adult Reconstructive Surgery State Key Laboratory of Pharmaceutical BiotechnologyThe Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical SchoolNanjingPR China Department of Biomedical Engineering School of MedicineTsinghua UniversityBeijingPR China Knee Surgery Department of the Institute of Sports Medicine Beijing Key Laboratory of Sports InjuriesPeking University Third HospitalBeijingPR China School of Stomatology Peking UniversityBeijingPR China National Institutes for Food and Drug Control BeijingPR China Department of Biomedical Engineering Institute of Future TechnologyPeking UniversityBeijingPR China

With the interdisciplinary convergence of biology,medicine and materials science,both research and clinical translation of biomaterials are progressing at a rapid ***,there is still a huge gap between applied basic research on biomaterials and their translational products-medical devices,where two significantly different perspectives and mindsets often work independently and non-synergistically,which in turn significantly increases financial costs and research *** this gap is well-known and often criticized in the biopharmaceutical industry,it is gradually *** this article,we critically examine the developmental pipeline of biodegradable biomaterials and biomaterial-based medical device *** based on clinical needs,market analysis,and relevant regulations,some ideas are proposed to integrate the two different mindsets to guide applied basic research and translation of biomaterial-based products,from the material and technical *** repair substitutes are discussed here as an ***,this will lay a strong foundation for biomaterial research and clinical translation,while reducing the amount of extra research effort and funding required due to the dissonance between innovative basic research and commercialization pipeline.

关键词： Biomaterials Polymer Translation medical devices Regulation Clinical needs

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Task Partition-Based Intelligent Offloading for Cache-Assisted Cloud-Edge Cooperation Networks

Task Partition-Based Intelligent Offloading for Cache-Assist...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Chao Fang Haizhen Luo Xiaoping Yang Haofei Xie Fangqing Tan Shu-Ming Tseng Mianxiong Dong Faculty of Information Technology Beijing University of Technology Beijing China Key Laboratory of Cognitive Radio and Information Processing Ministry of Education Guilin University of Electronic Technology Guilin China Key Laboratory of Industrial Internet of Things & Networked Control Chongqing University of Posts and Telecommunications Chongqing China Department of Electronic Engineering National Taipei University of Technology Taipei Taiwan Department of Sciences and Informatics Muroran Institute of Technology Muroran Japan

To satisfy the differentiated service requirements of delay-sensitive and computing-intensive tasks, it is urgent to efficiently allocate limited network resources to improve content distribution in cloud-edge environments. In this paper, we proposes a task partition-based intelligent offloading scheme to optimize resource allocation in cache-assisted cloud-edge cooperation environments. Specifically, we formulate the task partition-based optimal computation offloading problem as a latency minimization model in the cache-aided cloud-edge collaboration system. A new deep reinforcement learning (DRL) algorithm is designed to make optimal subtask offloading and resource allocation decisions based on current network state information, improving resource utilization and network delay. Simulation results demonstrate that the proposed model achieves lower-latency content delivery than the existing popular models in cache-enabled cloud-edge cooperation networks, and fast converges.

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MG-SLAM: Structure Gaussian Splatting SLAM with Manhattan World Hypothesis

arXiv

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arXiv 2024年

作者： Liu, Shuhong Deng, Tianchen Zhou, Heng Li, Liuzhuozheng Wang, Hongyu Wang, Danwei Li, Mingrui Department of Information Science and Technology Department of Complexity Science and Engineering The University of Tokyo Tokyo113-8654 Japan Institute of Medical Robotics Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Department of Mechanical Engineering Columbia University New York10027 United States School of Electrical and Electronic Engineering Nanyang Technological University Singapore Department of Computer Science Dalian University of Technology Dalian116024 China

Gaussian Splatting SLAMs have made significant advancements in improving the efficiency and fidelity of real-time reconstructions. However, these systems often encounter incomplete reconstructions in complex indoor environments, characterized by substantial holes due to unobserved geometry caused by obstacles or limited view angles. To address this challenge, we present Manhattan Gaussian SLAM, an RGB-D system that leverages the Manhattan World hypothesis to enhance geometric accuracy and completeness. By seamlessly integrating fused line segments derived from structured scenes, our method ensures robust tracking in textureless indoor areas. Moreover, The extracted lines and planar surface assumption allow strategic interpolation of new Gaussians in regions of missing geometry, enabling efficient scene completion. Extensive experiments conducted on both synthetic and real-world scenes demonstrate that these advancements enable our method to achieve state-of-the-art performance, marking a substantial improvement in the capabilities of Gaussian SLAM systems. © 2024, CC BY.

关键词： Gaussian distribution

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The role of input imaging combination and ADC threshold on segmentation of acute ischemic stroke lesion using U-Net

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European Radiology 2023年第9期33卷 6157-6167页

作者： Li, Ya-Hui Lin, Shao-Chieh Chung, Hsiao-Wen Chang, Chia-Ching Peng, Hsu-Hsia Huang, Teng-Yi Shen, Wu-Chung Tsai, Chon-Haw Lo, Yu-Chien Lee, Tung-Yang Juan, Cheng-Hsuan Juan, Cheng-En Chang, Hing-Chiu Liu, Yi-Jui Juan, Chun-Jung Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Department of Medical Imaging China Medical University Hsinchu Hospital No. 199 Sec. 1 Xinglong Rd. Zhubei City Hsinchu County 302 Hsinchu Taiwan Ph.D. Program in Electrical and Communication Engineering Feng Chia University Taichung Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan Department of Management Science National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Biomedical Engineering and Environmental Sciences National Tsing Hua University Hsinchu Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Radiology School of Medicine College of Medicine China Medical University Taichung Taiwan Department of Medical Imaging Medical University Hospital Taichung Taiwan Department of Neurology China Medical University Hospital Taichung Taiwan Cheng Ching Hospital Taichung Taiwan Master’s Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung Taiwan Department of Automatic Control Engineering Feng Chia University No. 100 Wenhwa Rd. Seatwen Taichung 40724 Taiwan Department of Biomedical Engineering The Chinese University of Hong Kong ERB1112 11/F William M.W. Mong Engineering Building N.T Shatin Hong Kong Multi-Scale Medical Robotics Center The Chinese University of Hong Kong N.T Shatin Hong Kong Department of Biomedical Engineering National Defense Medical Center Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan

Background: To evaluate the effect of the weighting of input imaging combo and ADC threshold on the performance of the U-Net and to find an optimized input imaging combo and ADC threshold in segmenting acute ischemic stroke (AIS) lesion. Methods: This study retrospectively enrolled a total of 212 patients having AIS. Four combos, including ADC-ADC-ADC (AAA), DWI-ADC-ADC (DAA), DWI-DWI-ADC (DDA), and DWI-DWI-DWI (DDD), were used as input images, respectively. Three ADC thresholds including 0.6, 0.8 and 1.8 × 10^–3 mm²/s were applied. Dice similarity coefficient (DSC) was used to evaluate the segmentation performance of U-Nets. Nonparametric Kruskal–Wallis test with Tukey–Kramer post-hoc tests were used for comparison. A p <.05 was considered statistically significant. Results: The DSC significantly varied among different combos of images and different ADC thresholds. Hybrid U-Nets outperformed uniform U-Nets at ADC thresholds of 0.6 × 10^–3 mm²/s and 0.8 × 10^–3 mm²/s (p <.001). The U-Net with imaging combo of DDD had segmentation performance similar to hybrid U-Nets at an ADC threshold of 1.8 × 10^–3 mm²/s (p =.062 to 1). The U-Net using the imaging combo of DAA at the ADC threshold of 0.6 × 10^–3 mm²/s achieved the highest DSC in the segmentation of AIS lesion. Conclusions: The segmentation performance of U-Net for AIS varies among the input imaging combos and ADC thresholds. The U-Net is optimized by choosing the imaging combo of DAA at an ADC threshold of 0.6 × 10^–3 mm²/s in segmentating AIS lesion with highest DSC. Key Points: • Segmentation performance of U-Net for AIS differs among input imaging combos. • Segmentation performance of U-Net for AIS differs among ADC thresholds. • U-Net is optimized using DAA with ADC = 0.6 × 10^–3mm²/s. © 2023, The Author(s), under exclusive licence to European Society of Radiology.

关键词： Deep Learning Diffusion Magnetic Resonance Imaging Ischemic Stroke Neural Networks, Computer Retrospective Study

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