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A Multi-staining Digital Pathology image Registration Method Based on Global and Local Computing

A Multi-staining Digital Pathology Image Registration Method...

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ACIS International conference on Software Engineering, Artificial Intelligence, Networking, and parallel/distributed Computing (SNPD)

作者： Yi Ding Xin Zhang Cheng Lu School of Computer and Cyber Sciences Communication University of China Beijing China Department of Radiology Guangdong Provincial People’s Hospital Guangzhou China

ISBN: (数字)9798350391954

ISBN: (纸本)9798350391961

To accurately evaluate the patient’s condition, medical workers usually need to register multiple pathological images of the lesion site samples. Using computer technology to assist in registration work can effectively improve the efficiency of doctors analyzing pathological images. One of the most advanced methods currently is the Virtual Alignment of Pathology image Series method, which is a multi-staining digital pathology image registration method that combines global and local calculations. However, this method may encounter certain biases when processing images with significant angle differences. Through a detailed analysis of this method, this article proposes an improvement plan which optimizes the acquisition of non-rigid registration mask images, enabling the method to obtain mask images more reasonably and achieve better registration results for images with significant angle differences. This provides more accurate judgment basis and helps doctors diagnose and develop treatment plans more accurately.

关键词： Pathology Solid modeling image registration Accuracy Medical services Software Registers

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A Hybrid Multi-Modal Medical image Fusion Technique using Optimal Sub-band Tree Structuring and Principal Component Analysis

A Hybrid Multi-Modal Medical Image Fusion Technique using Op...

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International conference on parallel distributed and Grid Computing (PDGC)

作者： Shailesh Bhosekar Prabhishek Singh Deepak Garg School of Computer Science and Artificial Intelligence SR University Warangal Telangana India School of Computer Science Engineering and Technology Bennett University Greater Noida India

ISBN: (数字)9798331521349

ISBN: (纸本)9798331521356

In image processing, "image fusion" is the amalgamation of attributes and requirements from many images into a singular, more comprehensive representation. Multi-modal medical image fusion is a significant category of image fusion. It entails the integration of medical images acquired from several modalities. This work utilizes computed tomography (CT) scans, Positron Emission Tomography (PET) and magnetic resonance imaging (MRI) as modalities. This study (M3IF-SBTS) aims to construct a multi modal medical image approach that combines Optimal Sub-band Tree Structuring (SBTS) and Principal Component Analysis (PCA) with MRI and CT images in a manner that maximizes the information content in the fused image. The SBTS is an advanced wavelet transform version of Discrete Wavelet Transform (DWT), where signal is filtered more times. The PCA provides dimensionality reduction and retains the relevant features. The wavelet coefficients are fused using PCA-based fusion method. This combination of SBTS and PCA provides superior results compared to using SBTS, DWT, or PCA as individual methods. This improves overall visual and parametric quality of fusion results than many compared methods.

关键词： Visualization Magnetic resonance imaging Computed tomography Information filters Discrete wavelet transforms Positron emission tomography image fusion Principal component analysis Biomedical imaging Wavelet coefficients

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CDCP: A Framework for Accelerating Dynamic Channel Pruning methods

CDCP: A Framework for Accelerating Dynamic Channel Pruning M...

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International conference on parallel and distributed Systems (ICPADS)

作者： Zhaohong Xiang Yigui Luo Yin Xie Haihong She Weiming Liang Laigang Zhao School of Software Engineering Tongji University Shanghai China Aichi Automobile (Shanghai) Company Limited

Dynamic channel pruning is a technique aimed at reducing the theoretical computational complexity and inference latency of convolutional neural networks. Dynamic channel pruning methods introduce complex additional modules for dynamically selecting channels for images. Due to the additional modules, dynamic channel pruning methods never achieve optimal acceleration effect in real world. To address this problem, we propose Consecutive Dynamic Channel Pruning (CDCP), a novel dynamic channel pruning framework unified for almost all dynamic pruning methods designed for continuous image processing. The core idea of CDCP stems from our observation that adjusting the network for all frames in semantically continuous scenes is unnecessary since adjacent frames often share similar network structures in dynamic channel pruning. CDCP introduces a simple binary classifier to determine whether the network structure needs to be adjusted for a new frame. Our method can also be used for semantically non-continuous image processing tasks with a slightly lower probability of model reuse. We validate the effectiveness of CDCP on three dynamic channel pruning methods and better acceleration effects are achieved when applied them with CDCP to the semantically continuous Waymo dataset, the nuScenes dataset, and the semantically discontinuous COCO dataset.

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Ancient Chinese Character image Retrieval Based on Fusing Deep Features and Skeleton Features

Ancient Chinese Character Image Retrieval Based on Fusing De...

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International conference on parallel and distributed Systems (ICPADS)

作者： Xinhui Wang Xuedong Tian School of Cyber Security and Computer Hebei University Baoding China Institute of Intelligent Image and Document Information Processing Hebei University Baoding China

The complex glyph structures and diverse writing styles of ancient Chinese character images lead to suboptimal performance when existing image retrieval methods are directly applied to datasets of these images. Addressing the impact on retrieval caused by the complex glyph structure and rich detail information characteristic of ancient Chinese character images, a multi-layer feature adaptive fusion model for ancient Chinese character image retrieval is designed. Firstly, a local feature extraction module is constructed to obtain low-level feature maps with different spatial receptive fields. Secondly, to better fuse features of varying scales, an improved ASFF(Adaptively Spatial Feature Fusion) method is employed to build the PSASFF(Pixel Shuffle Adaptively Spatial Feature Fusion) module for adaptive fusion of multi-layer features extracted by the designed network. Finally, in order to reduce the influence of the writing style of ancient Chinese characters on retrieval, the cosine similarity scores of image retrieval before and after fine processing are weighted and used as the ultimate similarity scores. The retrieval method proposed achieves an average retrieval accuracy of mAP@50 and mAP@30 of 0.8537 and 0.9576 respectively on the ancient Chinese character image dataset. Experimental results demonstrate the effectiveness of this method for ancient Chinese character image retrieval.

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MiDedup: A Restore-Friendly Deduplication Method on Docker image Storage Systems 20th

MiDedup: A Restore-Friendly Deduplication Method on Docker ...

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20th IFIP WG 10.3 International conference on Network and parallel Computing, NPC 2024

作者： Qin, Lisha Tan, Haoliang Zou, Xiangyu Ou, Wenhao Wei, Yan Huang, Rubing Xia, Wen Harbin Institute of Technology Shenzhen China Peng Cheng Laboratory Shenzhen China Zhongruan International Technology Service Co. Ltd. Shenzhen China Macau University of Science and Technology Macao China

ISBN: (纸本)9789819628292

Docker image storage systems, like Docker registry, often employ deduplication to reduce storage overhead. Existing deduplication methods for these systems detect redundancy at either layer or file level, each with its own advantages and limitations. Layer-level deduplication offers much faster restoration but lower deduplication ratio, as it eliminates duplicate layers while ignoring duplicate files across layers. Conversely, file-level deduplication offers a higher deduplication ratio but slower restoration, as removing duplicate files scatters the files of a layer, leading to multiple disk read I/O during restoration. Our analysis reveals that the slow restoration in file-level deduplication partly stems from ignoring file-layer relationships. In this paper, we propose MiDedup, a new Docker deduplication method. MiDedup detects redundancy at file-level and organizes files into a restore-friendly layout by considering file-layer relationships to enhance restore speed. Our studies also show that duplicated files of one layer are not uniformly distributed across different layers. MiDedup uses this insight to skip deduplicating scattered files to further optimize the file layout for faster restoration. Evaluations indicate that MiDedup achieves restore speeds that are 8–19× faster than file-level deduplication (slightly slower than layer-level one), while maintaining 9–47% higher deduplication ratios than layer-level deduplication. © IFIP International Federation for Information processing 2025.

关键词： Redundancy

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A Federated Content Distribution System to Build Health Data Synchronization Services 29

A Federated Content Distribution System to Build Health Data...

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29th Euromicro International conference on parallel, distributed and Network-Based processing (PDP)

作者： Carrizales-Espinoza, Diana Sanchez-Gallegos, Dante D. Gonzalez-Compean, J. L. Carretero, Jesus Cinvestav Tamaulipas Victoria Mexico Univ Carlos III Madrid Madrid Spain

ISBN: (纸本)9781665414555

In organizational environments, such as in hospitals, data have to be processed, preserved, and shared with other organizations in a cost-efficient manner. Moreover, organizations have to accomplish different mandatory non-functional requirements imposed by the laws, protocols, and norms of each country. In this context, this paper presents a Federated Content Distribution System to build infrastructure-agnostic health data synchronization services. In this federation, each hospital manages local and federated services based on a pub/sub model. The local services manage users and contents (i.e., medical imagery) inside the hospital, whereas federated services allow the cooperation of different hospitals sharing resources and data. Data preparation schemas were implemented to add non-functional requirements to data. Moreover, data published in the content distribution system are automatically synchronized to all users subscribed to the catalog where the content was published.

关键词： Data synchronization federated content distribution health data cloud computing

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Research and Suggestions for Evaluation Metrics of On-board Video Desensitization

Research and Suggestions for Evaluation Metrics of On-board ...

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Information Science, parallel and distributed Systems (ISPDS), International conference on

作者： Xiaolong Huang Te Hu Haojie Ji Yupeng Chen Wangdong Lu Peng He Guowei Sun Jingyan Wang State Key Laboratory of Intelligent Vehicle Safety Technology Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science & Technology University Beijing China Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science & Technology University Beijing China China Automotive Engineering Research Institute Co. Ltd Chongqing China Zhongtong Bus Holding Co. Ltd Liaocheng China

ISBN: (数字)9798350352719

ISBN: (纸本)9798350352726

Sensitive data leakage has become an urgent problem to be solved as more images based functionalities are being developed in vehicles. However, there is a scarcity of evaluation for on-board videos data desensitization. This research analyzes on-board video desensitization process including the image pre-processing stage, sensitive area localization stage and sensitive area desensitization stage. Considering that, this paper presents several evaluation methods and metrics of sensitive target detection performance, privacy-utility evaluation of video file metadata and image, so as to provide reference for the related research on the desensitization evaluation of on-board video.

关键词： Measurement Location awareness Information science Target recognition Current measurement distributed databases Object detection

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On the Evaluation of Two methods Applied to the Morphometry of Linear Dunes 21st

On the Evaluation of Two Methods Applied to the Morphometry ...

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21st International conference on image Analysis and processing (ICIAP)

作者： Schein, Tatiana Tais Emmendorfer, Leonardo R. NobreMendes, Fabiano Rodriguez, Barbara D. A. Almeida, Luis Pedro de Oliveira, Vinicius Menezes Univ Fed Rio Grande Programa Posgrad Modelagem Computac Rio Grande City Brazil Univ Fed Rio Grande Ctr Ciencias Computac BR-96203900 Rio Grande City Brazil Univ Fed Rio Grande Inst Matemat Estat & Fis BR-96203900 Rio Grande City Brazil CoLAB ATLANTIC Edificio LACSEstr Malveira Serra 920 P-2750834 Cascais Portugal

ISBN: (纸本)9783031064333;9783031064326

The evolution of dunes is a relevant topic in many areas, including the study of the marine environment. In particular, the widespread linear dunes are characterized by roughly parallel ridges, which extend for long distances. The identification of the main morphometric characteristics of linear dunes is a relevant topic, with wide applicability. This work evaluates two approaches for linear dune morphometry. The methods are built over the Radon transform, the Discrete Fourier Transform, and autocorrelation. The evaluation is performed over a set of publicly available dune images. Results show that the performance of the methods varies over the morphometric characteristics considered.

关键词： Dune morphology Morphometry Discrete Fourier Transform Radon transform Autocorrelation

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FERI: Feature Enhancement and Relational Interaction for image-text Matching

FERI: Feature Enhancement and Relational Interaction for Ima...

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International conference on parallel and distributed Systems (ICPADS)

作者： Yu Zhang Jianqiang Zhang Gongpeng Song Qin Lu Shuo Zhao Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China Shandong Branch of China Mobile Communication Group Design Institute Co. Jinan China

ISBN: (数字)9798331515966

ISBN: (纸本)9798331515973

image-text matching is an important problem at the intersection of computer vision and natural language processing. It aims to establish the semantic link between image and text to achieve high-quality semantic alignment between the two modalities. However, the existing methods have the problem that the meaning expressed in the image or the complex narrative in the text cannot be fully understood due to insufficient feature extraction. Moreover, due to the essential modal differences between images and texts, how to effectively and accurately align the semantic contents in images and texts has become the key of research. In order to solve the above problems, this paper proposes a method based on feature enhancement and relationship interaction. When processing images, the proposed method fuses labeled features, region features and location features to represent images. When processing text, a combination of Bi-GRU and self-attention mechanism is used to represent the text. In order to further align the semantic content in images and texts accurately, this paper improves two relational interaction mechanisms by identifying connection relationships and learning association relationships. Thus, the relation enhanced embedding is obtained. Finally, it calculated the similarity of the enhanced embedding to judge the matching degree of the image and text. Extensive experiments on the public datasets Flickr30K and MSCOCO demonstrate the effectiveness of our method.

关键词： Computer vision Fuses image matching Semantics Feature extraction Natural language processing

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image denoising based on Swin Transformer Residual Conv U-Net

Image denoising based on Swin Transformer Residual Conv U-Ne...

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ACIS International conference on Software Engineering, Artificial Intelligence, Networking, and parallel/distributed Computing (SNPD)

作者： Yong Gan Shaohui Zhou Haonan Chen Yuefeng Wang Zhengzhou University of Technology Zhengzhou China College of Computer Science and Technology Zhengzhou University of Light Industry Zhengzhou China

ISBN: (数字)9798350391954

ISBN: (纸本)9798350391961

In the field of computer vision, image denoising remains a fundamental and challenging problem, playing a crucial role in the preprocessing of various image processing tasks. The introduction of Convolutional Neural Networks (CNNs) into the image denoising domain has yielded significant improvements across different levels of visual tasks. In recent years, models based on the Swin Transformer have also been applied to the image denoising field, demonstrating superior denoising performance that surpasses CNN-based methods, thus becoming advanced techniques in current image denoising research. This paper proposes a Swin-Conv module that combines the local modeling capabilities of residual convolutional layers with the non-local modeling capabilities of the Swin Transformer and integrates this module into the UNet architecture for image denoising. For the dataset used in the model training process, data augmentation techniques were employed to randomly enhance the dataset, thereby improving overall robustness. The results indicate that the proposed Swin Transformer Residual Conv U-Net model shows improvement over current advanced networks, achieving PSNR and SSIM values of 36.09 and 0.963 at $\sigma=15,33.87$ and 0.915 at $\sigma=25$, and 28.96 and 0.810 at $\sigma=50$.

关键词： Training Visualization AWGN Computational modeling Noise reduction Transformers Data augmentation

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