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2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Shao, Wei Wang, Zhe Zhang, Ziming Zhou, Qinghua Wang, Ruoyu Tan, Wenjun Northeastern University Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Shenyang110189 China Affiliated Zhongshan Hospital of Dalian University Oncology Department Dalian116001 China

ISBN: (纸本)9781665468190

Segmenting the pulmonary airway in CT images to obtain its anatomical structure information can help doctors better understand the patient's condition and determine the treatment plan. However, due to the blurred boundary of the pulmonary airway in CT images, it has a high degree of overlap with the surrounding pulmonary parenchyma and other tissues, making segmentation difficult. In this paper, a method based on the separation of pulmonary airway in CT images is investigated. Based on the original U-net network, using the idea of migration learning, the U-net and VGG16 network with partially similar network structure are fused to form a VGG-Unet joint neural network, which not only accelerates the model training and image segmentation efficiency, but also ensures the accuracy of image segmentation. The experimental data source used CT images acquired from the partner hospital. The algorithm in this paper was used to segment and extract the CT images of airway of lungs with an accuracy of 86.52%, and the segmentation efficiency was high and stable. © 2022 IEEE.

关键词： image segmentation

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A Pulmonary Artery-Vein Separation algorithm based on the relationship between sub-trees 2020

A Pulmonary Artery-Vein Separation algorithm based on the re...

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The Fourth International Symposium on image computing and Digital Medicine

作者： Wenjun Tan Key Laboratory of Intelligent Computing in Medical Image Ministry of Education China

ISBN: (纸本)9781450389686

This article presents a combined algorithm of pulmonary artery-vein (A/V) separation considering both global and local information, including: the transformation of geometric graph, sub-tree separation, and A/V classification. During the process, geometric graphs are firstly built based on the centerlines; A separation of the adhesion points is performed by applying the information stored in the data structure of the nodes and links in the geometric graphs; Sub-trees are then combined according to the local and global information; The combined sub-trees are growing into vascular trees using 2D area growth method; And finally, classification of the arterial and venous vascular trees based on the knowledge of anatomy. An average accuracy of 85% has been achieved of the overall process with a processing time range between 40 s to 50 s, which indicates good performance and stability of this algorithm.

关键词： algorithm Artery-Vein Separation

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Appearance-order-based schema matching

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Journal of computing Science and Engineering 2014年第2期8卷 94-106页

作者： Ding, Guohui Cao, keyan Wang, Guoren Han, Dong Department of Computer Science Shenyang Aerospace University Shenyang China Key Laboratory of Medical Image Computing Ministry of Education Northeastern University Shenyang China College of Information Science and Engineering Northeastern University Shenyang China National Marine Data and Information Service Tianjin China

Schema matching is widely used in many applications, such as data integration, ontology merging, data warehouse and dataspaces. In this paper, we propose a novel matching technique that is based on the order of attributes appearing in the schema structure of query results. The appearance order embodies the extent of the importance of an attribute for the user examining the query results. The core idea of our approach is to collect statistics about the appearance order of attributes from the query logs, to find correspondences between attributes in the schemas to be matched. As a first step, we employ a matrix to structure the statistics around the appearance order of attributes. Then, two scoring functions are considered to measure the similarity of the collected statistics. Finally, a traditional algorithm is employed to find the mapping with the highest score. Furthermore, our approach can be seen as a complementary member to the family of the existing matchers, and can also be combined with them to obtain more accurate results. We validate our approach with an experimental study, the results of which demonstrate that our approach is effective, and has good performance. © 2014. The Korean Institute of Information Scientists and Engineers.

关键词： Data integration

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Adaptive delay-energy balanced partial offloading strategy in Mobile Edge computing networks

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Digital Communications and Networks 2023年第6期9卷 1310-1318页

作者： Shumei Liu Yao Yu Lei Guo Phee Lep Yeoh Branka Vucetic Yonghui Li School of Computer Science and Engineering Northeastern UniversityShenyang110819China Key Laboratory of Intelligent Computing in Medical Image Ministry of EducationNortheastern UniversityShenyang110819China School of Communication and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing400065China School of Electrical and Information Engineering University of SydneySydneyNSW2006Australia

Mobile Edge computing(MEC)-based computation offloading is a promising application paradigm for serving large numbers of users with various delay and energy *** this paper,we propose a flexible MECbased requirement-adaptive partial offloading model to accommodate each user's specific preference regarding delay and energy *** address the dimensional differences between time and energy,we introduce two normalized parameters and then derive the computational overhead of processing *** from existing works,this paper considers practical variations in the user request patterns,and exploits a flexible partial offloading mode to minimize computation overheads subject to tolerable delay,task workload and power *** the resulting problem is non-convex,we decouple it into two convex subproblems and present an iterative algorithm to obtain a feasible offloading *** experiments show that our proposed scheme achieves a significant improvement in computation overheads compared with existing schemes.

关键词： Mobile edge computing(MEC) Delay Energy consumption Dynamic balance Partial computation offloading

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EMD-based Adaptive Wavelet Threshold for Pulse Wave Denoising

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Chinese Journal of Biomedical Engineering(English Edition) 2015年第1期24卷 1-8页

作者： XU Li-shengl SHEN Yan-hua ZHONG Yue KANG Yan Max Q.-H.Meng Sino -Dutch Biomedical and Information Engineering School Northeastern University Key Laboratory of Medical Image Computing (Northeastern University) Ministry of Education Department of Electronic Engineering The Chinese University of Hong Kong

It is inevitable that noises will be introduced during the acquisition of pulse wave signal, which can result in morphology changes of the original pulse wave,and affect the hemodynamic analysis and diagnosis based on pulse wave signals. In order to remove these noises, an adaptive de-noising method based on empirical mode decomposition(EMD) and wavelet threshold is proposed in this paper. Compared with the wavelet threshold method for denoising pulse wave, the proposed approach is more effective, especially at low signal-to-noise ratio.

关键词： pulse wave de-noising EMD adaptive filter wavelet threshold

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Measure Oriented Cost-Sensitive SVM for 3D nodule detection

Measure Oriented Cost-Sensitive SVM for 3D nodule detection

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Peng Cao Dazhe Zhao Osmar Zaiane Key Laboratory of Medical Image Computing of Ministry of Education Northeastern University China

ISBN: (纸本)9781457702150

The class imbalance issue occurs when training a computer-aided detection (CAD) system for nodules. This imbalance causes poor prediction performance for true nodules. Moreover, the misclassification costs are different between two classes and high sensitivity of true nodules is essential in the detection. In order to eliminate or reduce the false positives while keeping high sensitivity, we present an effective wrapper framework incorporating the evaluation measure of imbalanced data into the objective function of cost sensitive SVM. We improve the performance of classification by simultaneously optimizing the best pair of misclassification cost parameter, feature subset and intrinsic parameters. We evaluated the method on a 3D Lung nodule dataset, showing that the proposed method outperforms many other exiting common methods, as well as specific imbalanced data learning methods, which indicates the effectiveness of our method on the imbalanced and unequal misclassification cost data classification.

关键词： Misclassification internal parameter False-positives Cost functions Objective function HIGH SENSITIVITY

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Virtually-Federated Scheduling of Parallel Real-Time Tasks 42

Virtually-Federated Scheduling of Parallel Real-Time Tasks

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42nd IEEE Real-Time Systems Symposium, RTSS 2021

作者： Jiang, Xu Guan, Nan Liang, Haochun Tang, Yue Qiao, Lei Yi, Wang Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University China City University of Hong Kong Hong Kong Beijing Institute of Control Engineering China Uppsala University Sweden

ISBN: (纸本)9781665428026

Federated scheduling is a promising approach to schedule parallel real-time tasks, where each task exclusively executes on a set of dedicated processors. However, federated scheduling suffers significant resource wasting since a task typically only uses part of the processing capacity allocated to it, while the unused part cannot be shared with other tasks. To solve this problem, we present a virtually-federated scheduling approach, which both enjoys the good analyzability of federated scheduling and allows tasks to efficiently share processors with others. The main idea is to construct virtual processors on physical processors, and let a task exclusively execute on a set of virtual processors. As a physical processor is shared by virtual processors, tasks effectively share processors with each other. On the other hand, as each task exclusively executes on its own virtual processor set, the good analyzability of federated scheduling can be carried into to our virtually-federated scheduling approach. We conduct comprehensive performance evaluation to compare our proposed approach with existing methods of different types. Experiment results show that our approach consistently outperforms existing methods to a considerable extent under a wide range of parameter settings. ©2021 IEEE

关键词： Scheduling

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The analysis and development of computed 2D optical flow velocity based on phantom data

The analysis and development of computed 2D optical flow vel...

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2012 International Conference on Computerized Healthcare, ICCH 2012

作者： Cai, Fuyu Triest, Han Van Kang, Yan Sino-Dutch Biomedical and Information Engineering School Northeastern University Shenyang City Liaoning Province 110004 China Key Laboratory of Medical Image Computing Northeastern University Ministry of Education United States

ISBN: (纸本)9781467351294

Optical Flows is the study of the relationship with image intensity changes in time and the motion of objects. In this paper, the gradient-based optical flow method is studied to determine the velocity of observed objects and the parameters which can influence the accuracy of the velocity are identified and discussed. According to the characteristics of this Algorithm, an improved iterative method is proposed to let the method be more flexible to ground truth data. To understand the principles behind this phenomenon, we create a phantom sequence to analyze and experiment the algorithm from both mathematical and geometrical aspect. The precision of our method can reach an excellent level with a fast computing speed. The experiments on the phantom images showed that the method work quickly and accurately. © 2012 IEEE.

关键词： Optical flows

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CAB: Empathetic Dialogue Generation with Cognition, Affection and Behavior 28th

CAB: Empathetic Dialogue Generation with Cognition, Affecti...

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28th International Conference on Database Systems for Advanced Applications, DASFAA 2023

作者： Gao, Pan Han, Donghong Zhou, Rui Zhang, Xuejiao Wang, Zikun School of Computer Science and Engineering Northeastern University Shenyang China Key Laboratory of Intelligent Computing in Medical Image of Ministry of Education Northeastern University Shenyang China Swinburne University of Technology Hawthorn Australia

ISBN: (纸本)9783031306747

Empathy is an important characteristic to be considered when building a more intelligent and humanized dialogue agent. However, existing methods did not fully comprehend empathy as a complex process involving three aspects: cognition, affection and behavior. In this paper, we propose CAB, a novel framework that takes a comprehensive perspective of cognition, affection and behavior to generate empathetic responses. For cognition, we build paths between critical keywords in the dialogue by leveraging external knowledge. This is because keywords in a dialogue are the core of sentences. Building the logic relationship between keywords, which is overlooked by the majority of existing works, can improve the understanding of keywords and contextual logic, thus enhance the cognitive ability. For affection, we capture the emotional dependencies with dual latent variables that contain both interlocutors’ emotions. The reason is that considering both interlocutors’ emotions simultaneously helps to learn the emotional dependencies. For behavior, we use appropriate dialogue acts to guide the dialogue generation to enhance the empathy expression. Extensive experiments demonstrate that our multi-perspective model outperforms the state-of-the-art models. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Knowledge management

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Multi-scale cyclical similarity prototype refinement for few-shot breast ultrasound image segmentation 17

Multi-scale cyclical similarity prototype refinement for few...

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17th IEEE International Conference on Signal Processing, ICSP 2024

作者： Ou, Yingfeng Yang, Xing Zhang, Jian Jian, Caiqing Wang, Lihui College of Computer Science and Technology Guizhou University Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province State Key Laboratory of Public Big Data Engineering Research Center of Text Computing Ministry of Education Guiyang China

ISBN: (纸本)9798350387384

Few-shot learning based methods can address the reliance on large-scale labeled samples in current breast tumor segmentation. However, previous methods typically rely on a few support samples to extract abstract, coarse-grained semantic prototypes, without considering the interaction between support and query data. In this study, we aim to provide each query image with relevant and information-rich support information. By integrating the difficult point selection module and the multi-scale cyclical prototype refinement module, we progressively refine coarse-grained support prototypes into more informative, fine-grained class prototypes, thereby better matching the highly variable breast ultrasound query data. Experiments on two datasets demonstrate that our proposed multi-scale cyclical similarity prototype refinement network (CSPRNet) achieves remarkable improvements compared to previous state-of-the-art methods. Specifically, using ResNet50 as the backbone, we achieve 57.93%/57.92% and 57.58%/59.24% mIoU for 1-shot and 5-shot segmentation, respectively, on public and private datasets, outperforming the suboptimal method by 8.18%/2.55% and 2.77%/4.48%. © 2024 IEEE.

关键词： Ultrasonic imaging

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