International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)
2024 17th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)
26-28 Oct. 2024
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Proceedings The 2024 17th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics
Publication Year: 2024,Page(s):1 - 1
Proceedings The 2024 17th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics
Research on Low-Temperature Storage Refrigeration Technology Based on Factors of Biological Sample Damage
Mingyu Zheng;Kun Zhou;Yongsheng Hu;Xinyue Yao;Guo Yuan;Rui Ning;Yansong Fan
Publication Year: 2024,Page(s):1 - 6
This paper explores refrigeration technologies for the low-temperature storage of biological samples, specifically focusing on damage factors affecting these samples. It systematically analyzes current refrigeration techniques, highlighting adverse factors encountered during low-temperature storage of biological samples. It presents the strengths and weaknesses of various refrigeration technologie...Show More
Influence Level Assessment in Suppressing the Spread of Undesirable Information in Online Social Networks
Publication Year: 2024,Page(s):1 - 5
Undesirable information can spread rapidly in social networks and cause great damage. This paper introduces an innovative Priority Recovery Control (PRC-SIRS) model aimed at curbing the dissemination of undesirable information. In this model, infected nodes are not left to heal spontaneously. Instead, network administrators strategically prioritize the blocking of infected nodes with the greatest ...Show More
CBCTformer: Transformer Model for Sparse-View CBCT Artifact Reduction in Image-Guided Radiotherapy
Publication Year: 2024,Page(s):1 - 5
This study proposes a Transformer-based image domain model, named CBCTformer, for artifact reduction in sparse-view cone-beam computed tomography (CBCT) used in image-guided radiotherapy (IGRT). The CBCTformer model is built on a Swin Transformer U-Net architecture, comprising both encoder and decoder components. The model was trained, validated, and tested on CBCT data from 163, 30, and 30 real p...Show More
In virtual worlds and robotic teleoperation scenarios, this sense of touch must be artificially reconstructed by stimulation of the human body (usually by the hand) to produce the haptic features required for enhanced realism and human performance. With the development of virtual reality and augmented reality technologies, interacting directly with virtual objects with haptic feedback is receiving...Show More
Lower Extremity CT Segmentation for Patients with Knee Osteoarthritis Based on 3D U-Net
Publication Year: 2024,Page(s):1 - 5
Total Knee Arthroplasty (TKA) is the most effective treatment for end-stage Knee Osteoarthritis (KOA). Preoperative planning using the patient's CT images can significantly improve the performance of the surgery. During the preoperative planning process, segmenting the femur and tibia, especially knee joint regions, and extracting 3D models are crucial steps. Deep learning methods such as U-Net pr...Show More
A Real-Time GPU-Based Framework for Curved Array Ultrafast Ultrasound Doppler Imaging
Publication Year: 2024,Page(s):1 - 7
Doppler flow imaging is a hybrid imaging method with 2D and Doppler images. The traditional dual-type segment scanning sequence has limited real-time display frame rate and ensemble size. Ultrafast Doppler imaging improves sensitivity to low-velocity microfluidic by providing a higher frame rate and relieving the problem of limited ensemble size. However, the uniform-type continuous scanning seque...Show More
ConvCycleGAN - An Unsupervised Generative Adversarial Network for Chinese Pastoral Painting Style
Publication Year: 2024,Page(s):1 - 5
The image style conversion work is to map the style of the target domain image while keeping the content of the natural landscape image in the source domain unchanged. This technology is widely used in fields such as painting, film, and artistic creation. At present, research in this field mostly focuses on learning the styles of Western painters, lacking research on traditional Chinese painting s...Show More
Combining Multi-Scale Feature Fusion and Attention Mechanism to Achieve Pulmonary Nodule Classification
Publication Year: 2024,Page(s):1 - 6
Lung cancer is the deadliest form of cancer, with most cases originating from small malignant nodules. However, the early symptoms of malignant nodules are not obvious, which can lead to misdiagnosis and delay the optimal treatment time. Therefore, differentiating between benign and malignant lung nodules is crucial for the early diagnosis and treatment of lung cancer. The advent of convolutional ...Show More
UAVs Flight Planning Method for Multi-Scan Corridor Coverage in Remote Sensing Areas
Mingzhi Wei;Chunming Yang;Kangsheng Dong;Yao Huang;Xianwei Jiang;Lingfeng Liu
Publication Year: 2024,Page(s):1 - 6
In order to address the issue of achieving comprehensive coverage in corridor scanning path planning for unmanned aerial vehicles (UAVs) in multi-area mapping, a Dual-Sequence Multi-Scan Corridor Planning Method (DSMCPM) is proposed. In the initial stage of the process, the scanning corridors that encompass multiple areas are identified as essential flight segments. A dual-sequence encoding is app...Show More
ITRScore: A Multi-Granularity Evaluation Method for Image-Text Retrieval Models Based on LLM
Publication Year: 2024,Page(s):1 - 6
In current cross-modal image-text retrieval evaluation, there are often struggles with capturing fine-grained matches between images and texts using existing methods. This limitation leads to a poor correlation between evaluation results and human judgement. To address this, we propose a novel evaluation method for ITR models called ITRScore. This method simulates the human evaluation process by c...Show More
Revealing the Fairness Issues of Text-to-Image Generation Models Based on Metamorphic Testing
Publication Year: 2024,Page(s):1 - 6
The Text-to-Image Generation(T2I) Models acquires implicit social biases during the training process, which can easily cause social disputes and negative impacts in sensitive fields such as news broadcasting, educational illustrations, and so on. There are many factors contributing to this situation. Most of the existing studies only focus on the combed biases of gender and skin color. Therefore, ...Show More
Deep Learning-Based Denoising With Noise Power Spectrum and CycleGAN in Low-Dose Head CT Images
Publication Year: 2024,Page(s):1 - 4
Head Computed Tomography (CT) is a crucial diagnostic tool in neurological imaging. While low-dose computed tomography (LDCT) aims to minimize radiation exposure, it presents challenges in balancing noise reduction with detail preservation, particularly for head CT where small anatomical structures are vital. This study proposes a deep learning-based denoising technique to enhance the quality of h...Show More
Postural Synergy Analysis of Continuous Hand Movements for Application to Prosthetic Hands
Hai Jiang;Yusuke Yamanoi;Peiji Chen;Xu Yong;Guanglin Li;Hiroshi Yokoi;Xiaobei Jing
Publication Year: 2024,Page(s):1 - 6
This paper focuses on exploring the coordinated movements used to control dexterous myoelectric prosthetic hands by hand motion analysis inspired by the motor synergy theory of the human hand. Recently, prosthetic hands have become multi-degree-of-freedom, and simultaneous proportional control of each finger is the most required challenge. In response to this problem, motor synergy is expected to ...Show More
A Deep Residual Network-Based Model for Image Steganography Analysis
Fei He;Renchao Qin;Keqiang Tan;Lan Zhang;Jianlin Long;Jialin Duan;Suonan Li
Publication Year: 2024,Page(s):1 - 6
Steganalysis is the process of detecting and analyzing steganography, which is widely utilized in fields such as network security, copyright protection, military, and intelligence. To address the challenges of existing steganalysis models, particularly their difficulty in capturing subtle steganographic information and the low detection rates for adaptive steganography algorithms, this paper propo...Show More
AT2D: An Automated Testing Framework for Deepfake Detection Models
Minghao Yuan;Yong Fan;Ya Pan;Yang Chao;Gangcheng Ji;Wenfeng Zhong
Publication Year: 2024,Page(s):1 - 6
Deepfake videos are rapidly spreading across the internet, posing significant threats to public interests. To counter this issue, researchers have developed various deep learning-based deepfake detection methods, which have demonstrated excellent performance. However, these detection methods are typically evaluated based on relevant benchmarks that often fail to fully reflect the complexity of rea...Show More
LRCu: A High-Performance Parallel Program for Identifying Hub Genes
Publication Year: 2024,Page(s):1 - 6
The LeaderRank algorithm identifies influential nodes using the idea of the random walk and performs well in the identification of hub genes in biological networks. The rapid development of biological technologies promotes the evolution of networks to be highly complex and increasing largely in size. In this study, we introduce LRCu, for computing LeaderRank using CUDA, to identify hub genes. The ...Show More
Light Detection and Ranging (LiDAR) has been widely used in various fields in recent years, and the resulting large amount of point cloud data storage has become an issue to be solved. To solve this problem, the commonly used point cloud coordinate $(x,\ y,\ z)$ is transformed to the spherical coordinate $(r,\ \omega,\ \alpha)$ in this paper. We then construct the so-called two-dimensional slices,...Show More
Power Spectral Analysis of Different Electroencephalogram Frequency Bands for Epileptic Seizures Induced by Electroconvulsive Therapy in Rats
Dongkai Tian;Jin Li;Changjiang He;Hui Zhang;Jiyue Zhao;Yu Chang;Deliang Luo;Xiangmei Chen;Han Yang;Xiang Chen
Publication Year: 2024,Page(s):1 - 6
The quality of epileptic seizures plays a crucial role in evaluating the efficacy of electroconvulsive therapy (ECT). However, due to differences in individual anatomical structures and treatment modes, the electroencephalographic (EEG) signals during epileptic seizures exhibit significant diversity in both the time and frequency domains. This study induced different patterns of epileptic seizures...Show More
A Novel Fractional-Order Model of Medium-Frequency Respiratory Impedance
Hongwei Wang;Bin Li;Hongqiang Mo;Yuanda Xu;Zhaoxiang Xu;Yanqing Xie
Publication Year: 2024,Page(s):1 - 6
Respiratory impedance in the medium-frequency range reflects the dynamic properties of airways and lung tissues, and plays an important role in the early diagnosis of pulmonary diseases. Fractional-order models can characterize complex dynamics with fewer parameters compared to integer-order models, and have been used to represent the medium-frequency characteristics of the respiratory impedance. ...Show More
Obtaining 6d attitude information of a target object from a single RGB image can provide accurate environment awareness and localization capabilities for an aircraft, thereby improving mission execution efficiency and success, while reducing risk and increasing safety. Aiming at the problem that the existing pose estimation algorithms have low accuracy in the small error range in the pose estimati...Show More
Dynamical Coupling for Cardiopulmonary-Cerebral Resuscitation Using Recurrence-Based Analyses
Yuanbo Zhang;Qiao Han;Yuguo Chen;Feng Xu;Jiali Wang;Yafei Guo;Ke Li
Publication Year: 2024,Page(s):1 - 6
Cardiopulmonary resuscitation (CPR), as the emergency treatment of cardiac arrest (CA) patients, its quality is directly linked to patient survival rates and the recovery of neurological function. However, the physiological monitoring indicators widely used in current clinical practice often exist in isolation, thus making it difficult to comprehensively reveal the complex interaction mechanisms a...Show More
A Novel Rehabilitation Training System for Hand Amputation Based on Mixed Reality
Publication Year: 2024,Page(s):1 - 6
Hand loss impacts physical, mental, and social aspects of individuals' lives. Prosthetics offer a crucial pathway to regaining lost functionality. However, challenges such as phantom limb pain, discomfort, and high abandonment rates persist. This study introduces a rehabilitation system that combines mixed reality with prosthetic hand. The virtual interface includes four buttons, each triggered by...Show More
Priority-Aware Task Offloading and UAV Trajectory Optimization for Aerial Access Network - Assisted Mobile Edge Computing
Publication Year: 2024,Page(s):1 - 8
With the surge in computational data, Mobile Edge Computing (MEC) is set to become a crucial technology for reducing communication latency and congestion. However, the widespread adoption of MEC faces several challenges. Aerial Access Networks (AANs), comprising hierarchical High Altitude Platforms (HAPs) and low-altitude Unmanned Aerial Vehicles (UAVs), offer a groundbreaking framework for MEC ta...Show More
Analysis of Typical Features Using an Angle-to-sEMG Decoder Model
Zehao Liu;Hai Jiang;Yusuke Yamanoi;Peiji Chen;Xiaobei Jing;Guanglin Li;Hiroshi Yokoi;Xu Yong
Publication Year: 2024,Page(s):1 - 6
Current prosthetic control methods mainly rely on extensive data collection and the training of classification models. Nevertheless, achieving a balance between learning efficiency and classification accuracy remains a persistent challenge. In this paper, we introduce a novel prosthetic control approach that divides the processing of surface electromyography (sEMG) signals into two stages to predi...Show More
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