生物医学工程学杂志最新文献_第10页

[Brain magnetic resonance image registration based on parallel lightweight convolution and multi-scale fusion]. [基于并行轻量级卷积和多尺度融合的脑磁共振图像配准]。

生物医学工程学杂志 Pub Date : 2024-04-25 DOI: 10.7507/1001-5515.202309014

Yu Shen, Yuan Yan, Jing Song, Guanghui Liu, Jiawen Xu, Ziyi Wei

{"title":"[Brain magnetic resonance image registration based on parallel lightweight convolution and multi-scale fusion].","authors":"Yu Shen, Yuan Yan, Jing Song, Guanghui Liu, Jiawen Xu, Ziyi Wei","doi":"10.7507/1001-5515.202309014","DOIUrl":"https://doi.org/10.7507/1001-5515.202309014","url":null,"abstract":"Medical image registration plays an important role in medical diagnosis and treatment planning. However, the current registration methods based on deep learning still face some challenges, such as insufficient ability to extract global information, large number of network model parameters, slow reasoning speed and so on. Therefore, this paper proposed a new model LCU-Net, which used parallel lightweight convolution to improve the ability of global information extraction. The problem of large number of network parameters and slow inference speed was solved by multi-scale fusion. The experimental results showed that the Dice coefficient of LCU-Net reached 0.823, the Hausdorff distance was 1.258, and the number of network parameters was reduced by about one quarter compared with that before multi-scale fusion. The proposed algorithm shows remarkable advantages in medical image registration tasks, and it not only surpasses the existing comparison algorithms in performance, but also has excellent generalization performance and wide application prospects.","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"41 2","pages":"213-219"},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11058484/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140865354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

[Design and support performance evaluation of medical multi-position auxiliary support exoskeleton mechanism]. [医用多位置辅助支撑外骨骼机构的设计与支撑性能评估]。

生物医学工程学杂志 Pub Date : 2024-04-25 DOI: 10.7507/1001-5515.202210040

Kaicheng Qi, Zhiyang Yin, Jianjun Zhang, Jingke Song, Gaokun Qiao

{"title":"[Design and support performance evaluation of medical multi-position auxiliary support exoskeleton mechanism].","authors":"Kaicheng Qi, Zhiyang Yin, Jianjun Zhang, Jingke Song, Gaokun Qiao","doi":"10.7507/1001-5515.202210040","DOIUrl":"https://doi.org/10.7507/1001-5515.202210040","url":null,"abstract":"Aiming at the status of muscle and joint damage caused on surgeons keeping surgical posture for a long time, this paper designs a medical multi-position auxiliary support exoskeleton with multi-joint mechanism by analyzing the surgical postures and conducting conformational studies on different joints respectively. Then by establishing a human-machine static model, this study obtains the joint torque and joint force before and after the human body wears the exoskeleton, and calibrates the strength of the exoskeleton with finite element analysis software. The results show that the maximum stress of the exoskeleton is less than the material strength requirements, the overall deformation is small, and the structural strength of the exoskeleton meets the use requirements. Finally, in this study, subjects were selected to participate in the plantar pressure test and biomechanical simulation with the man-machine static model, and the results were analyzed in terms of plantar pressure, joint torque and joint force, muscle force and overall muscle metabolism to assess the exoskeleton support performance. The results show that the exoskeleton has better support for the whole body and can reduce the musculoskeletal burden. The exoskeleton mechanism in this study better matches the actual working needs of surgeons and provides a new paradigm for the design of medical support exoskeleton mechanism.","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"41 2","pages":"295-303"},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11058496/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140856150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

[A study of cognitive impairment quantitative assessment method based on gait characteristics]. [基于步态特征的认知障碍定量评估方法研究]。

生物医学工程学杂志 Pub Date : 2024-04-25 DOI: 10.7507/1001-5515.202305019

Shuai Tao, Hongbin Hu, Liwen Kong, Zeping Lyu, Zumin Wang, Jie Zhao, Shuang Liu

{"title":"[A study of cognitive impairment quantitative assessment method based on gait characteristics].","authors":"Shuai Tao, Hongbin Hu, Liwen Kong, Zeping Lyu, Zumin Wang, Jie Zhao, Shuang Liu","doi":"10.7507/1001-5515.202305019","DOIUrl":"https://doi.org/10.7507/1001-5515.202305019","url":null,"abstract":"Alzheimer's disease (AD) is a common and serious form of elderly dementia, but early detection and treatment of mild cognitive impairment can help slow down the progression of dementia. Recent studies have shown that there is a relationship between overall cognitive function and motor function and gait abnormalities. We recruited 302 cases from the Rehabilitation Hospital Affiliated to National Rehabilitation Aids Research Center and included 193 of them according to the screening criteria, including 137 patients with MCI and 56 healthy controls (HC). The gait parameters of the participants were collected during performing single-task (free walking) and dual-task (counting backwards from 100) using a wearable device. By taking gait parameters such as gait cycle, kinematics parameters, time-space parameters as the focus of the study, using recursive feature elimination (RFE) to select important features, and taking the subject's MoCA score as the response variable, a machine learning model based on quantitative evaluation of cognitive level of gait features was established. The results showed that temporal and spatial parameters of toe-off and heel strike had important clinical significance as markers to evaluate cognitive level, indicating important clinical application value in preventing or delaying the occurrence of AD in the future.","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"41 2","pages":"281-287"},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11058505/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140872731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

[A review on electroencephalogram based channel selection]. [基于脑电图的通道选择综述]。

生物医学工程学杂志 Pub Date : 2024-04-25 DOI: 10.7507/1001-5515.202308034

Xiangzhe Li, Dan Wang, Baiwen Zhang, Chaojie Fan, Jiaming Chen, Meng Xu, Yuanfang Chen

引用次数: 0

[Identifying spatial domains from spatial transcriptome by graph attention network]. [通过图注意网络从空间转录组识别空间域]。

生物医学工程学杂志 Pub Date : 2024-04-25 DOI: 10.7507/1001-5515.202304030

Hanwen Wu, Jie Gao

引用次数: 0

[Reconstruction of elasticity modulus distribution base on semi-supervised neural network]. [基于半监督神经网络的弹性模量分布重构]。

生物医学工程学杂志 Pub Date : 2024-04-25 DOI: 10.7507/1001-5515.202306008

Xiao Zhang, Bo Peng, Rui Wang, Xingyue Wei, Jianwen Luo

{"title":"[Reconstruction of elasticity modulus distribution base on semi-supervised neural network].","authors":"Xiao Zhang, Bo Peng, Rui Wang, Xingyue Wei, Jianwen Luo","doi":"10.7507/1001-5515.202306008","DOIUrl":"https://doi.org/10.7507/1001-5515.202306008","url":null,"abstract":"Accurate reconstruction of tissue elasticity modulus distribution has always been an important challenge in ultrasound elastography. Considering that existing deep learning-based supervised reconstruction methods only use simulated displacement data with random noise in training, which cannot fully provide the complexity and diversity brought by in-vivo ultrasound data, this study introduces the use of displacement data obtained by tracking in-vivo ultrasound radio frequency signals (i.e., real displacement data) during training, employing a semi-supervised approach to enhance the prediction accuracy of the model. Experimental results indicate that in phantom experiments, the semi-supervised model augmented with real displacement data provides more accurate predictions, with mean absolute errors and mean relative errors both around 3%, while the corresponding data for the fully supervised model are around 5%. When processing real displacement data, the area of prediction error of semi-supervised model was less than that of fully supervised model. The findings of this study confirm the effectiveness and practicality of the proposed approach, providing new insights for the application of deep learning methods in the reconstruction of elastic distribution from in-vivo ultrasound data.","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"41 2","pages":"262-271"},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11058507/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140869863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

[Microwave Heartprint: A novel non-contact human identification technology based on cardiac micro-motion detection using ultra wideband bio-radar]. [微波心脏指纹：基于超宽带生物雷达心脏微动探测的新型非接触式人体识别技术]。

生物医学工程学杂志 Pub Date : 2024-04-25 DOI: 10.7507/1001-5515.202309068

Wei Huang, Wei Ren, Kehan Wang, Zhao Li, Jianqi Wang, Guohua Lu, Fugui Qi

{"title":"[Microwave Heartprint: A novel non-contact human identification technology based on cardiac micro-motion detection using ultra wideband bio-radar].","authors":"Wei Huang, Wei Ren, Kehan Wang, Zhao Li, Jianqi Wang, Guohua Lu, Fugui Qi","doi":"10.7507/1001-5515.202309068","DOIUrl":"https://doi.org/10.7507/1001-5515.202309068","url":null,"abstract":"The existing one-time identity authentication technology cannot continuously guarantee the legitimacy of user identity during the whole human-computer interaction session, and often requires active cooperation of users, which seriously limits the availability. This study proposes a new non-contact identity recognition technology based on cardiac micro-motion detection using ultra wideband (UWB) bio-radar. After the multi-point micro-motion echoes in the range dimension of the human heart surface area were continuously detected by ultra wideband bio-radar, the two-dimensional principal component analysis (2D-PCA) was exploited to extract the compressed features of the two-dimensional image matrix, namely the distance channel-heart beat sampling point (DC-HBP) matrix, in each accurate segmented heart beat cycle for identity recognition. In the practical measurement experiment, based on the proposed multi-range-bin & 2D-PCA feature scheme along with two conventional reference feature schemes, three typical classifiers were selected as representatives to conduct the heart beat identification under two states of normal breathing and breath holding. The results showed that the multi-range-bin & 2D-PCA feature scheme proposed in this paper showed the best recognition effect. Compared with the optimal range-bin & overall heart beat feature scheme, our proposed scheme held an overall average recognition accuracy of 6.16% higher (normal respiration: 6.84%; breath holding: 5.48%). Compared with the multi-distance unit & whole heart beat feature scheme, the overall average accuracy increase was 27.42% (normal respiration: 28.63%; breath holding: 26.21%) for our proposed scheme. This study is expected to provide a new method of undisturbed, all-weather, non-contact and continuous identification for authentication.","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"41 2","pages":"272-280"},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11058502/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140865994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

[A survey on the application of convolutional neural networks in the diagnosis of occupational pneumoconiosis]. [卷积神经网络在职业性尘肺病诊断中的应用调查]。

生物医学工程学杂志 Pub Date : 2024-04-25 DOI: 10.7507/1001-5515.202309079

Yu Wang, Jiang Wu, Dongsheng Wu

{"title":"[A survey on the application of convolutional neural networks in the diagnosis of occupational pneumoconiosis].","authors":"Yu Wang, Jiang Wu, Dongsheng Wu","doi":"10.7507/1001-5515.202309079","DOIUrl":"10.7507/1001-5515.202309079","url":null,"abstract":"Pneumoconiosis ranks first among the newly-emerged occupational diseases reported annually in China, and imaging diagnosis is still one of the main clinical diagnostic methods. However, manual reading of films requires high level of doctors, and it is difficult to discriminate the staged diagnosis of pneumoconiosis imaging, and due to the influence of uneven distribution of medical resources and other factors, it is easy to lead to misdiagnosis and omission of diagnosis in primary healthcare institutions. Computer-aided diagnosis system can realize rapid screening of pneumoconiosis in order to assist clinicians in identification and diagnosis, and improve diagnostic efficacy. As an important branch of deep learning, convolutional neural network (CNN) is good at dealing with various visual tasks such as image segmentation, image classification, target detection and so on because of its characteristics of local association and weight sharing, and has been widely used in the field of computer-aided diagnosis of pneumoconiosis in recent years. This paper was categorized into three parts according to the main applications of CNNs (VGG, U-Net, ResNet, DenseNet, CheXNet, Inception-V3, and ShuffleNet) in the imaging diagnosis of pneumoconiosis, including CNNs in pneumoconiosis screening diagnosis, CNNs in staging diagnosis of pneumoconiosis, and CNNs in segmentation of pneumoconiosis foci to conduct a literature review. It aims to summarize the methods, advantages and disadvantages, and optimization ideas of CNN applied to the images of pneumoconiosis, and to provide a reference for the research direction of further development of computer-aided diagnosis of pneumoconiosis.","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"41 2","pages":"413-420"},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11058508/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140863616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

[Medical image segmentation data augmentation method based on channel weight and data-efficient features]. [基于通道权重和数据高效特征的医学图像分割数据增强方法]。

生物医学工程学杂志 Pub Date : 2024-04-25 DOI: 10.7507/1001-5515.202302024

Xing Wu, Chenjie Tao, Zhi Li, Jian Zhang, Qun Sun, Xianhua Han, Yanwei Chen

{"title":"[Medical image segmentation data augmentation method based on channel weight and data-efficient features].","authors":"Xing Wu, Chenjie Tao, Zhi Li, Jian Zhang, Qun Sun, Xianhua Han, Yanwei Chen","doi":"10.7507/1001-5515.202302024","DOIUrl":"https://doi.org/10.7507/1001-5515.202302024","url":null,"abstract":"In computer-aided medical diagnosis, obtaining labeled medical image data is expensive, while there is a high demand for model interpretability. However, most deep learning models currently require a large amount of data and lack interpretability. To address these challenges, this paper proposes a novel data augmentation method for medical image segmentation. The uniqueness and advantages of this method lie in the utilization of gradient-weighted class activation mapping to extract data efficient features, which are then fused with the original image. Subsequently, a new channel weight feature extractor is constructed to learn the weights between different channels. This approach achieves non-destructive data augmentation effects, enhancing the model's performance, data efficiency, and interpretability. Applying the method of this paper to the Hyper-Kvasir dataset, the intersection over union (IoU) and Dice of the U-net were improved, respectively; and on the ISIC-Archive dataset, the IoU and Dice of the DeepLabV3+ were also improved respectively. Furthermore, even when the training data is reduced to 70 %, the proposed method can still achieve performance that is 95 % of that achieved with the entire dataset, indicating its good data efficiency. Moreover, the data-efficient features used in the method have interpretable information built-in, which enhances the interpretability of the model. The method has excellent universality, is plug-and-play, applicable to various segmentation methods, and does not require modification of the network structure, thus it is easy to integrate into existing medical image segmentation method, enhancing the convenience of future research and applications.","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"41 2","pages":"220-227"},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140858513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

[Research advances of biomedical polymeric microneedles for non-transdermal local drug delivery]. [用于非透皮局部给药的生物医学聚合物微针的研究进展]。

生物医学工程学杂志 Pub Date : 2024-04-25 DOI: 10.7507/1001-5515.202307038

Haiyan Li, Hongjuan Han, Lu Wang, Jingzhi Yao, Wenqian Xiao, Bo Li

{"title":"[Research advances of biomedical polymeric microneedles for non-transdermal local drug delivery].","authors":"Haiyan Li, Hongjuan Han, Lu Wang, Jingzhi Yao, Wenqian Xiao, Bo Li","doi":"10.7507/1001-5515.202307038","DOIUrl":"10.7507/1001-5515.202307038","url":null,"abstract":"Microneedles have emerged as the new class of local drug delivery system that has broad potential for development. Considering that the microneedles can penetrate tissue barriers quickly, and provide localized and targeted drug delivery, their applications have gradually expanded to non-transdermal drug delivery recently, which are capable of providing rapid and effective treatment for injuries and diseases of organs or tissues. However, a literature search revealed that there is a lack of summaries of the latest developments in non-transdermal drug delivery research by using biomedical polymeric microneedles. The review first described the materials and fabrication methods for the polymeric microneedles, and then reviewed a representative application of microneedles for non-transdermal drug delivery, with the primary focus being on treating and repairing the tissues or organs such as oral cavity, ocular tissues, blood vessels and heart. At the end of the article, the opportunities and challenges associated with microneedles for non-transdermal drug delivery were discussed, along with its future development, in order to provide reference for researchers in the relevant field.","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"41 2","pages":"406-412"},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140868344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0