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Rethinking Polyp Segmentation from the Perspectives of Matching Views and Seeking Camouflage

Multimedia Systems 2025年第3期31卷 1-17页

作者： Jiang, Zhengfang Chen, Haipeng Yang, Yongping Liu, Xianzhu Lyu, Yingda College of Software Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China College of Computer Science and Technology Jilin University Changchun130012 China Department of Colorectal Anal Surgery The Second Hospital of Jilin University Changchun130022 China National and Local Joint Engineering Research Center of Space Optoelectronics Technology Changchun University of Science and Technology Changchun130022 China College of Opto-Electronic Engineering Changchun University of Science and Technology Changchun130022 China Public Computer Education and Research Center Jilin University Changchun130012 China

Accurate segmentation of polyps from colonoscopy images is of great significance for the prevention of colorectal cancer. Despite notable progress, polyp segmentation remains a challenging task due to the diversity of polyp size and shape, as well as the camouflage property of polyps caused by their high similarity to surrounding tissues. To address these challenges, inspired by human perceptual experience in finding objects, we propose a multi-perspective collaborative network (MPCNet), innovatively identifying the potential polyps from the perspectives of matching views and seeking camouflage. Firstly, from the former perspective, a global–local aware module is proposed to provide various feature receptive fields to match suitable views for polyps of different sizes and shapes. Then, from the latter perspective, a texture enhancement module (TEM) and an interaction refinement module (IRM) are proposed to mine and complement clues essential for breaking the camouflage. Specifically, TEM mines texture-related clues and amplifies the subtle texture differences between polyps and their background, while IRM complements boundary clues and further optimizes feature representation through the interaction between boundaries and regions, thereby generating accurate segmentation results with complete regions and fine boundaries. Extensive experiments on five benchmark polyp datasets show that our MPCNet outperforms other state-of-the-art methods. In particular, we achieve a mean Dice of 81.7% and 82.4% on the most challenging datasets CVC-ColonDB and ETIS, respectively, which are significantly higher than competing methods. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Image segmentation

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Field-assisted spin-polarized electron transport through a single quantum well with spin-orbit coupling

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Chinese Physics B 2012年第3期21卷 389-394页

作者：丁秀欢张存喜王瑞周运清孔令民 Department of Mathematics Zhejiang Ocean University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Department of Physics Zhejiang Ocean University

We have investigated theoretically the field-driven electron transport through a single-quantum-well semiconductor heterostructure with spin-orbit coupling. The splitting of the asymmetric Fano-type resonance peaks due to the Dresselhaus spin-orbit coupling is found to be highly sensitive to the direction of the incident electron. The splitting of the Fano-type resonance induces the spin-polarization dependent electron current. The location and the line shape of the Fano-type resonance can be controlled by adjusting the energy and the direction of the incident electron, the oscillation frequency, and the amplitude of the external field. These interesting features may be used to devise tunable spin filters and realize pure spin transmission currents.

关键词： Fano resonance Floquet channel spin-orbit coupling

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A fast rigid registration algorithm for medical images

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Journal of Fiber Bioengineering and Informatics 2014年第3期7卷 409-418页

作者： Feng, Yuncong Li, Xiongfei Zhang, Xiaoli Ding, Tienan Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun China Department of Computer Science and Technology Changchun China

Image registration is a vital research branch in medical image processing and analysis. In this paper, we proposed a new framework for rigid medical image registration. It can also be regarded as a pre-processing of non-rigid image registration algorithms. The interest of the algorithm lies in its simplicity and high e±ciency. In the registration algorithm, we firstly segmented the reference image and °oat image into two parts: tissue parts and background parts. Then the centers of the two images were located through performing distance transform on the two segmented tissue images. Finally, we detected the longest radius of the two tissue regions, by which we determined the rotating angle. We tested the registration algorithm on dozens of medical images, and the experimental results show us that the algorithm is competent for medical image registration.

关键词： Image registration

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UAV Swarm-enabled Collaborative Post-disaster Communications in Low Altitude Economy via a Two-stage Optimization Approach

arXiv

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arXiv 2025年

作者： Zheng, Xiaoya Sun, Geng Li, Jiahui Wang, Jiacheng Wu, Qingqing Niyato, Dusit Jamalipour, Abbas College of Computer Science d Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China College of Computing and Data Science Nanyang Technological University 639798 Singapore College of Computing and ta Science Nanyang Technological University 639798 Singapore Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China School of Electrical and Computer Engiering The University of Sydney SydneyNSW2006 Australia

The low-altitude economy (LAE), as a new economic paradigm, plays an indispensable role in cargo transportation, healthcare, infrastructure inspection, and especially post-disaster communication. Specifically, unmanned aerial vehicles (UAVs), as one of the core technologies of the LAE, can be deployed to provide communication coverage, facilitate data collection, and relay data for trapped users, thereby significantly enhancing the efficiency of post-disaster response efforts. However, conventional UAV self-organizing networks exhibit low reliability in long-range cases due to their limited onboard energy and transmit ability. Therefore, in this paper, we design an efficient and robust UAV-swarm enabled collaborative self-organizing network to facilitate post-disaster communications. Specifically, a ground device transmits data to UAV swarms, which then use collaborative beamforming (CB) technique to form virtual antenna arrays and relay the data to a remote access point (AP) efficiently. Then, we formulate a rescue-oriented post-disaster transmission rate maximization optimization problem (RPTRMOP), aimed at maximizing the transmission rate of the whole network. Given the challenges of solving the formulated RPTRMOP by using traditional algorithms, we propose a two-stage optimization approach to address it. In the first stage, the optimal traffic routing and the theoretical upper bound on the transmission rate of the network are derived. In the second stage, we transform the formulated RPTRMOP into a variant named V-RPTRMOP based on the obtained optimal traffic routing, aimed at rendering the actual transmission rate closely approaches its theoretical upper bound by optimizing the excitation current weight and the placement of each participating UAV via a diffusion model-enabled particle swarm optimization (DM-PSO) algorithm. Simulation results show the effectiveness of the proposed two-stage optimization approach in improving the transmission rate of the construct

关键词： Unmanned aerial vehicles (UAV)

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Error Formulas for Lagrange Projectors Determined by Cartesian Sets

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Journal of Systems Science & Complexity 2018年第4期31卷 1090-1102页

作者： LI Zhe ZHANG Shugong DONG Tian GONG Yihe School of Science Changchun University of Science and Technology Changchun 130022 China Key Laboratory of Symbolic Computation and Knowledge Engineering Jilin University Changchun 130012 China School of Mathematics Key Laboratory of Symbolic Computation and Knowledge Engineering (Ministry of Education) Jilin University Changchun 130012 China Northeast Electric Power University Jilin 132012 China School of Mathematics Jilin University Changchun 130012 China

This paper studies error formulas for Lagrange projectors determined by Cartesian sets. Cartesian sets are properly subgrids of tensor product grids. Given interpolated functions with all order continuous partial derivatives, the authors directly construct the good error formulas for Lagrange projectors determined by Cartesian sets. Owing to the special algebraic structure, such a good error formula is useful for error estimate.

关键词： Cartesian sets error formulas ideal interpolation multivariate polynomial interpolation

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Improvement of escape time algorithm by no- escape-point

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Journal of Computers 2011年第8期6卷 1648-1653页

作者： Liu, Shuai Che, Xiangjiu Wang, Zhengxuan College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China

Escape time algorithm is a universal algorithm when to create fractal image. A class of algorithms based on escape time algorithm is wasting-calculation. In this essay, when combined with the feature of eventually periodic point of functions, we define a kind of points as no-escape point. To analyze the shortcomings of the classic algorithm, we improve the escape time algorithm base on the no-escape points. We analyze the algorithm and put forward the best application scope for it. By create lots of fractal figures, we find the figures created by the two algorithms are consistent with each other except a few escape points. We compare the complexity between the two algorithms and find the iteration times by the improved algorithm are less than escape time algorithm when creating the fractal images. We do several experiments and find the improved algorithm is universal and it reduces the time-consuming. © 2011 ACADEMY PUBLISHER.

关键词： Fractals

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A Novel Locomotion Rule Rmbedding Long Short-Term Memory Network with Attention for Human Locomotor Intent Classification Using Multi-Sensors Signals

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Computers, Materials & Continua 2024年第6期79卷 4349-4370页

作者： Jiajie Shen Yan Wang Dongxu Zhang Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of EducationColleague of Computer Science and TechnologyJilin UniversityChangchun130012China College of Software and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of EducationJilin UniversityChangchun130012China

Locomotor intent classification has become a research hotspot due to its importance to the development of assistive robotics and wearable *** work have achieved impressive performance in classifying steady locomotion ***,it remains challenging for these methods to attain high accuracy when facing transitions between steady locomotion *** to the similarities between the information of the transitions and their adjacent steady ***,most of these methods rely solely on data and overlook the objective laws between physical activities,resulting in lower accuracy,particularly when encountering complex locomotion modes such as *** address the existing deficiencies,we propose the locomotion rule embedding long short-term memory(LSTM)network with Attention(LREAL)for human locomotor intent classification,with a particular focus on transitions,using data from fewer sensors(two inertial measurement units and four goniometers).The LREAL network consists of two levels:One responsible for distinguishing between steady states and transitions,and the other for the accurate identification of locomotor *** classifier in these levels is composed of multiple-LSTM layers and an attention *** introduce real-world motion rules and apply constraints to the network,a prior knowledge was added to the network via a rule-modulating *** method was tested on the ENABL3S dataset,which contains continuous locomotion date for seven steady and twelve transitions *** results showed that the LREAL network could recognize locomotor intents with an average accuracy of 99.03%and 96.52%for the steady and transitions states,*** is worth noting that the LREAL network accuracy for transition-state recognition improved by 0.18%compared to other state-of-the-art network,while using data from fewer sensors.

关键词： Lower-limb prosthetics deep neural networks motion classification

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A novel method for computing the inverse of cardinal direction relations

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Journal of Convergence Information Technology 2012年第1期7卷 130-138页

作者： Wang, Fang Liu, Dayou Dong, Yiqun College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education

This paper focuses efforts on the problem of computing the inverse of cardinal direction relations (CRs), which is a fundamental problem in qualitative spatial reasoning. We study the quite expressive cardinal direction relation model for extended objects, known as cardinal direction calculus (CDC). We first concentrate on a set of a special type of CRs defined in CDC, named rectangle-CRs, and compute the inverse of rectangle-CRs by exploiting the evident connection between basic rectangle- CRs and interval relations. Then, we consider progressively the general cardinal direction relations in CDC, or called CDC relations for short, the inverse of which is computed by reducing to the computation of the inverse of rectangle-CRs. This simplifies the computations. Analyzing in theory and the final results both demonstrate that our algorithms are correct and complete and the time complexity is bounded by a constant number of operations.

关键词： Calculations

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Tuning the Learning Rate for Stochastic Variational Inference

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Journal of Computer Science & Technology 2016年第2期31卷 428-436页

作者： Xi-Ming Li Ji-Hong Ouyang College of Computer Science and Technology Jilin University Changchun 130000 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130000 China

Stochastic variational inference （SVI） can learn topic models with very big corpora. It optimizes the variational objective by using the stochastic natural gradient algorithm with a decreasing learning rate. This rate is crucial for SVI; however, it is often tuned by hand in real applications. To address this, we develop a novel algorithm, which tunes the learning rate of each iteration adaptively. The proposed algorithm uses the Kullback-Leibler （KL） divergence to measure the similarity between the variational distribution with noisy update and that with batch update, and then optimizes the learning rates by minimizing the KL divergence. We apply our algorithm to two representative topic models： latent Dirichlet allocation and hierarchical Dirichlet process. Experimental results indicate that our algorithm performs better and converges faster than commonly used learning rates.

关键词： stochastic variational inference online learning adaptive learning rate topic model

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Improved CS Algorithm and its Application in Parking Space Prediction

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Journal of Bionic engineering 2020年第5期17卷 1075-1083页

作者： Rui Guo Xuanjing Shen Hui Kang College of Computer Science and Technology Jilin UniversityChangchun 130012China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin UniversityChangchun 130012China

This paper simulates the cuckoo incubation process and flight path to optimize the Wavelet Neural Network(WNN)model,and proposes a parking prediction algorithm based on WNN and improved Cuckoo Search(CS)***,the initialization parameters are provided to optimize the WNN using the improved *** traditional CS algorithm adopts the strategy of overall update and evaluation,but does not consider its own information,so the convergence speed is very *** proposed algorithm employs the evaluation strategy of group update,which not only retains the advantage of fast convergence of the dimension-by-dimension update evaluation strategy,but also increases the mutual relationship between the nests and reduces the overall running ***,we use the WNN model to predict parking *** proposed algorithm is compared with six different heuristic algorithms in five *** experimental results show that the proposed algorithm is superior to other algorithms in terms of running time and accuracy.

关键词： wavelet neural network cuckoo search algorithm available parking spaces prediction bionic

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