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检索条件"任意字段=International Congress on Image and Signal Processing, BioMedical Engineering and Informatics"

共 2036 条记录，以下是241-250 订阅

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Adaptive signal Denoising of Fiber-Optic Gyroscope Based on Improved Current Statistical Model 15

Adaptive Signal Denoising of Fiber-Optic Gyroscope Based on ...

引用

15th international congress on image and signal processing, biomedical engineering and informatics, CISP-BMEI 2022

作者： Zhang, Yejun Jin, Wenguang College of Information Science and Electronic Engineering Zhejiang University Hangzhou China Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province Hangzhou China

ISBN: (数字)9781665488877

ISBN: (纸本)9781665488877

As the core sensor of inertial navigation system (INS), the random noise of fiber-optic gyro (FOG) will reduce the accuracy of INS. In order to process the random noise of FOG, an adaptive Kalman filtering (AKF) algorithm based on innovation sequence combined with the improved current statistical model (ICSM) is proposed. The introduction of ICSM algorithm avoids the complicated data processing of time series modeling. Integrate with the model, an AKF algorithm based on innovation sequence is proposed. Experimental results show that the random noise of FOG can be effectively reduced by ICSM and AKF based on innovation sequence. © 2022 IEEE.

关键词： Inertial navigation systems

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A Power Separation Fast Response Brown-Out Detection Structure 15

A Power Separation Fast Response Brown-Out Detection Structu...

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15th international congress on image and signal processing, biomedical engineering and informatics, CISP-BMEI 2022

作者： Liang, Shiming Diao, Shengxi School of Communication and Electronic Engineering East China Normal University Shanghai China

ISBN: (数字)9781665488877

ISBN: (纸本)9781665488877

This work presents a brown-out detection circuit architecture with the most reported selectable reference levels, which can work in a wide temperature range. Compared with reported BOD circuits, the proposed BOD circuit separates the power supply of brown-out detection and functional circuit from the external power supply, which gives higher robustness. The proposed architecture is implemented in a 12 nm CMOS process, occupying a 0.01 mm- Area. The post layout simulation shows that the circuit can realize a detection delay within 1us in the temperature range of -40-125°C © 2022 IEEE.

关键词： Delay circuits

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Exploring Gender Differences Based on Functional Magnetic Resonance images by Deep Learning and Gradient-weighted Class Activation Mapping 16

Exploring Gender Differences Based on Functional Magnetic Re...

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16th international congress on image and signal processing, biomedical engineering and informatics, CISP-BMEI 2023

作者： Luo, Jie Bin Chao Ma, Ji Wang, Yan Jiang Chen, Xue College of Control Science and Engineering Qingdao China Qingdao University The Institute for Digital Medicine and Computer-Assisted Surgery Qingdao China

ISBN: (纸本)9798350330755

Previous studies have shown gender differences in cognitive function and the prevalence of some neurological diseases. Understanding gender differences in functional connectivity (FC) will provide a new perspective for understanding these differences. We wanted to develop an effective model for the gender prediction and identify the major source of gender differences in functional connectivity. In this study we used FC generated from functional Magnetic Resonance Imaging (fMRI) from the Human Connectome Project in 1038 healthy subjects. We apply deep learning to test whether functional connectivity networks can effectively predict gender and identify the main sources of gender differences in FC. The accuracy of predicting gender by using the functional connectivity network has reached more than 90%, and we found that there are significant gender differences in the FC of interhemispheric brain areas and the FC in the right hemisphere, and in addition to the previously discovered default mode network (DMN), frontoparietal network (FPN), somatomotor network (SMN), there were gender differences in visual network (VIN), auditory network (AUN), and dorsal attention network (DAN) as well, and the gender differences within each resting-state network (RSN) were also large. Our results suggest that gender differences exist in functional connectivity networks and certain subnetworks can be focused on when studying gender-related cognitive functions and neurological disorders. © 2023 IEEE.

关键词： Magnetic resonance imaging

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Impact of Ionospheric Phase Perturbation on Sea Clutter Spectrum in the Sky-Surface Wave Passive Radar

Impact of Ionospheric Phase Perturbation on Sea Clutter Spec...

引用

international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Tao Ying Shuaiqi Wang Cheng Zhou Xiaoyang Hou College of Electronic Engineering Naval University of Engineering Wuhan China

ISBN: (数字)9798331507398

ISBN: (纸本)9798331507404

In the Sky-Surface Wave Passive Radar, the iono-spheric phase Perturbation can change the spectrum of sea clutter and reduce the detection performance of the system. To solve this problem, this paper starts with the influence mechanism of ionospheric phase Perturbation on the sea clutter spectrum, constructs the sea clutter spectrum model under the ionospheric Perturbation interference, and carries on the simulation and analysis.

关键词： Passive radar Analytical models Perturbation methods Biological system modeling signal processing Clutter informatics Ionosphere Electrons biomedical engineering

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A Virtual Staining Method for Immunohistochemical images of Breast Cancer 16

A Virtual Staining Method for Immunohistochemical Images of ...

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16th international congress on image and signal processing, biomedical engineering and informatics, CISP-BMEI 2023

作者： Duan, Guanhua Cao, Yankun Guo, Wei Cui, Lizhen Liu, Zhi Shandong University School of Information Science and Engineering Qingdao266237 China Shandong University School of Software Jinan250101 China

ISBN: (纸本)9798350330755

Breast cancer is a common malignant cancer. Detection of human epidermal growth factor receptor 2 (HER2) status based on immunohistochemistry (IHC) is an effective method for breast cancer diagnosis. Early diagnosis and treatment in breast cancer can greatly reduce the mortality rate, but the immunohistochemistry-based staining method is time-consuming and expensive. For the standpoint of saving labor, resources and time costs, direct generation of virtual IHC images based on hematoxylin and eosin (HE) slices is an efficient and accurate method. We proposed an IHC image generation method based on generative adversarial network (GAN). A content encoder, a style encode and a discriminator were used in our method, the first encoder of which extracted unstained images in the generator, the second encoder which obtained a stained style to stain unstained images to generate IHC images, and the discriminator of which is designed to judge the authenticity and the classification of HER2 expression at the same time. Experiments showed that our method outperforms other methods in PSNR and SSIM metrics in BCI dataset. © 2023 IEEE.

关键词： Generative adversarial networks

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Evaluation of Glymphatic System Activity by Diffusion Tensor image in Mild Traumatic Brain Injury 16

Evaluation of Glymphatic System Activity by Diffusion Tensor...

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16th international congress on image and signal processing, biomedical engineering and informatics, CISP-BMEI 2023

作者： Wu, Bixia Tan, Hui Zhang, Gengbiao Zheng, Wenbin The Second Affiliated Hospital of Shantou University Medical College Department of Radiology Guangdong Shantou China

ISBN: (纸本)9798350330755

To investigate the value of diffusion tensor image analysis along the perivascular space(DTI-ALPS) index on glymphatic system activity in mild traumatic brain injury(mTBI) patients. The study included 28 healthy control participants (HC) (mean age, 34 years) and 28 mTBI patients (mean age, 36 years). The clinical information(including the results of Glasgow Coma Scale(GCS), Montreal Cognitive Assessment(MOCA) and Rivermead behavioral memory test) and MRI data of each subjects were complete. The diffusivity along the perivascular spaces, as well as association and projection fibers, were analyzed to create a diffusivity along the perivascular space index (DTI-ALPS index). Then, we evaluated the variations in the index of ALPS between the HC and mTBI groups, and further correlation analysis between the DTI-ALPS index and clinical features in mTBI patients was carried out. Compared to the HC group, the mTBI group's ALPS-index values were noticeably lower. [median, whole brain: 1.452 vs. 1.593 (P=0.005);left brain: 1.457 vs. 1.616 (P=0.006);right brain: 1.451 vs. 1.605 (P=0.027)]. Left brain Dyproj values were considerably higher in mTBI patients than in healthy controls (P=0.005). The correlation analysis of the DTI-ALPS index with the GCS, MoCA and Rivermead score in the mTBI group was not statistically significant. DTI-ALPS index can be used to evaluate impairment of the lymphatic system in mTBI patients, which has a good prospect for exploring the pathogenesis of mTBI. © 2023 IEEE.

关键词： Diffusion tensor imaging

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Tuberculosis detection based on cough sounds: a multi-model voting mechanism 16

Tuberculosis detection based on cough sounds: a multi-model ...

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16th international congress on image and signal processing, biomedical engineering and informatics, CISP-BMEI 2023

作者： Bao, Xiaofan Xu, Wenlong Pan, Chen Liu, Wenlong Lou, Xiaomin Chen, Yuanyuan Zhao, Xiaoqiang Zhang, Chenlu Liu, Feng China Jiliang University School of Information Engineering Hangzhou China Hangzhou Red Cross Hospital Information Section Hangzhou China University of Queensland School of Information Technology and Electrical Engineering BrisbaneQLD Australia

ISBN: (纸本)9798350330755

Tuberculosis (TB) is one of the deadliest infectious diseases and the 13th leading cause of death worldwide. Because of its infectivity, screening in crowded places is particularly important. Although the PPD test, which is currently commonly used for community screening, has the advantage of simplicity and low cost compared to other TB detection methods such as IGRA and X-rays, the high number of false positives does not allow it to be used as a mass screening method. To address these issues, this paper proposes a computer-assisted screening-based method that can differentiate between normal individuals and TB patients by cough sounds. We designed a multi-model voting mechanism to test the classification of 1000 cough tone segments. The experiments were conducted by soft-voting tests with different weight assignments for three models: the resnet50 model, the improved Googlenet model, and the fusion model of Bi-LSTM fused with Googlenet. After averaging 10 cross-validations, the experimental results showed that screening for TB using cough sounds could achieve better results, obtaining 98.05% accuracy, 98.82% sensitivity, and 97.49% specificity. At the same time, this screening method has the advantages of non-invasiveness, repeatable detection, and low cost, which can be applied to the initial screening of crowded places such as communities. © 2023 IEEE.

关键词： Diagnosis

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Cervical Cancer Screening on Multi-class Imbalanced Cervigram Dataset using Transfer Learning 15

Cervical Cancer Screening on Multi-class Imbalanced Cervigra...

引用

15th international congress on image and signal processing, biomedical engineering and informatics, CISP-BMEI 2022

作者： Saini, Manisha Susan, Seba Delhi Technological University Department of Computer Science and Engineering New Delhi India Delhi Technological University Department of Information Technology New Delhi India

ISBN: (数字)9781665488877

ISBN: (纸本)9781665488877

image classification from a multi-class imbalanced dataset is challenging because it is difficult to detect all the minority classes present in the datasets. In this paper, the authors have extended their recently introduced work on a novel deep learning neural network for binary-class imbalanced datasets, called VGGIN-Net, by applying it to classify different grades of cervical cancer from a multi-class imbalanced dataset having a small number of samples. The experimental results prove that the proposed approach along with the data augmentation and rejection resampling is effective for multi-class imbalanced datasets. As analyzed through extensive experiments on a benchmark cervical screening dataset, the proposed approach in comparison to the other state-of-the-art approaches is vividly proven to be a more efficient method. © 2022 IEEE.

关键词： Diseases

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A Unity-Gain Buffer with 1.6GHz Bandwidth and 1900V/μs Slew Rate based on an OPA Adopting Cascaded Class-AB Structure 15

A Unity-Gain Buffer with 1.6GHz Bandwidth and 1900V/μs Slew...

引用

15th international congress on image and signal processing, biomedical engineering and informatics, CISP-BMEI 2022

作者： Wang, Xueping Zhu, Xiaorui Diao, Shengxi School of Communication and Electronic Engineering East China Normal University Shanghai China

ISBN: (纸本)9781665488877

A wideband and high slew rate (SR) unity-gain buffer (UGB) with the capability to drive a heavy load is proposed in this brief. An operational amplifier (OPA) is configured as unity gain negative feedback to improve the bandwidth and gain accuracy. A complementary input stage and cascaded class-AB output stage are adopted to enhance the small-signal bandwidth and SR of the OPA. The UGB is implemented in the $0.18-\mu\mathrm{m}$ SiGe BiCMOS technology and achieves a -3 dB bandwidth of 1.6 GHz, and an average SR of $1900\ \mathrm{V}/\mu\mathrm{s}$ with 5 V supply voltage and $100\ \Omega$ load resistance. The quiescent current of the core amplifier is 3.8 mA. © 2022 IEEE.

关键词： Operational amplifiers

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An Iterative Majorization-Minimization Approach to Deep Denoiser-Plugged image Inpainting 15

An Iterative Majorization-Minimization Approach to Deep Deno...

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15th international congress on image and signal processing, biomedical engineering and informatics, CISP-BMEI 2022

作者： Zhao, Hengyuan Shao, Wenze Zhu, Fukun Yan, Peng Ge, Qi Miao, Zhuang College of Telecom. and Inform. Engineering Nanjing University of Posts and Telecommunications Nanjing China College of Command and Control Engineering Army Engineering University Nanjing China

ISBN: (数字)9781665488877

ISBN: (纸本)9781665488877

It is known notoriously that most deep learning-based computer vision models are black-boxes. In this paper, a preliminary attempt has been made, deriving an interpretable representation learning approach to a specific inverse imaging problem, i.e., image inpainting. The new approach is not only rooted in the classical optimization framework, but also closely connected to the numerical differential equations. What is more important, numerous experimental results demonstrate that the proposed approach has achieved comparable or even better performance than many cutting-edge restoration algorithms, particularly those based on either sparse representation or naïve deep representation. © 2022 IEEE.

关键词： Inverse problems

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