生物医学工程学杂志最新文献_第8页

[MSCNet: Coronary artery segmentation network with multi-scale cascade encoding and dynamic spatial context enhancement]. [MSCNet：基于多尺度级联编码和动态空间上下文增强的冠状动脉分割网络]。

生物医学工程学杂志 Pub Date : 2026-06-25 DOI: 10.7507/1001-5515.202407087

An Zeng, Xianhang Cheng, Dan Pan, Jiayu Ye

{"title":"[MSCNet: Coronary artery segmentation network with multi-scale cascade encoding and dynamic spatial context enhancement].","authors":"An Zeng, Xianhang Cheng, Dan Pan, Jiayu Ye","doi":"10.7507/1001-5515.202407087","DOIUrl":"10.7507/1001-5515.202407087","url":null,"abstract":"Coronary artery segmentation is a critical step in the clinical diagnosis of coronary heart disease. To tackle segmentation breaks and false segmentation caused by the thin and complex coronary vessels as well as the severe foreground-background imbalance in computed tomography angiography images, this paper proposes MSCNet, a coronary artery segmentation network with multi-scale cascade encoding and dynamic spatial context enhancement. The network constructed a multi-scale cascaded encoder using Swin Transformer and large-kernel convolutions. It sequentially modeled and fused multi-scale features by capturing long-range dependencies and local details, and reparameterized large-kernel convolutions via a spatial frequency matrix to strengthen fine detail capture. Meanwhile, a spatial transformer module was designed to dynamically guide multi-head attention learning and optimize decoding performance. On the ImageCAS dataset, MSCNet achieved an average Dice coefficient of 81.24%, which was 3.57%, 3.78%, and 3.85% higher than 3D UX-Net, SwinUNETR, and SegMamba, respectively. MSCNet effectively improves the accuracy of coronary artery segmentation and provides support for clinical evaluation.","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 3","pages":"479-486"},"PeriodicalIF":0.0,"publicationDate":"2026-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13311052/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148346662","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

[Research on auditory neurofeedback technology and its multi-disciplinary applications]. [听觉神经反馈技术及其多学科应用研究]。

生物医学工程学杂志 Pub Date : 2026-06-25 DOI: 10.7507/1001-5515.202505004

Xiuyan Hu, Anmin Gong, Xinyu Shi, Bowen Gong, Sinan Li, Ting Shi, Yunfa Fu

引用次数: 0

[Deep learning-driven high-frequency ultrasound method for skin aging assessment]. [深度学习驱动的高频超声皮肤老化评估方法]。

生物医学工程学杂志 Pub Date : 2026-06-25 DOI: 10.7507/1001-5515.202510021

Xiaofang Zhang, Bingbing He, Dongjie Sun, Haiyan Li, Ningtao Zhang, Yufeng Zhang

{"title":"[Deep learning-driven high-frequency ultrasound method for skin aging assessment].","authors":"Xiaofang Zhang, Bingbing He, Dongjie Sun, Haiyan Li, Ningtao Zhang, Yufeng Zhang","doi":"10.7507/1001-5515.202510021","DOIUrl":"10.7507/1001-5515.202510021","url":null,"abstract":"Ultraviolet radiation is a primary external factor contributing to skin photoaging, as it induces cellular deoxyribonucleic acid damage and collagen degeneration, thereby accelerating skin aging and increasing the risk of skin cancer. Currently, skin aging assessment mainly relies on dermatologists' empirical judgment, which is inherently subjective and inefficient. To address these limitations, this study proposes a deep learning-driven intelligent skin aging classification method based on high-frequency ultrasound images. The proposed model employs efficient network version 2 (EfficientNetV2) as the backbone network and introduces the Gaussian error linear unit (GELU) activation function and layer normalization to enhance nonlinear feature representation and training stability. In addition, a global-aware temporal hierarchical network is integrated to enable efficient multi-scale feature extraction of skin tissue. A dual enhancement attention mechanism, combining parallel channel-spatial attention and squeeze-and-excitation modules, is further designed to improve the model's sensitivity to key aging-related regions. Moreover, a multi-scale path dropout regularization strategy is adopted to effectively alleviate overfitting. Experiments conducted on a facial high-frequency ultrasound dataset collected from subjects aged 25~55 years demonstrate that the proposed method achieves an accuracy of 87.66%, a precision of 88.27%, a recall of 87.66%, an F1 score of 87.80%, and a specificity of 97.94%, consistently outperforming existing mainstream models. These results indicate that the proposed approach enables high-precision identification of skin aging levels and provides an efficient and objective auxiliary diagnostic tool for skincare, anti-aging treatment, and the prevention of photoaging-related skin diseases.","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 3","pages":"487-495"},"PeriodicalIF":0.0,"publicationDate":"2026-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13311050/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148346595","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

[Research on electrical impedance tomography for pediatric pneumonia based on an improved radial basis function neural network]. [基于改进径向基函数神经网络的小儿肺炎电阻抗断层扫描研究]。

生物医学工程学杂志 Pub Date : 2026-06-25 DOI: 10.7507/1001-5515.202512072

Ruiqi Wang, Chengtao Yu, Yang Wu, Jiafeng Yao, Huaiyan Wang, Li Ding

{"title":"[Research on electrical impedance tomography for pediatric pneumonia based on an improved radial basis function neural network].","authors":"Ruiqi Wang, Chengtao Yu, Yang Wu, Jiafeng Yao, Huaiyan Wang, Li Ding","doi":"10.7507/1001-5515.202512072","DOIUrl":"10.7507/1001-5515.202512072","url":null,"abstract":"In the diagnosis of pediatric pneumonia, the weak conductivity contrast of lung tissues leads to limited image resolution in electrical impedance tomography (EIT). To improve the quality of image reconstruction, this study proposes a radial basis function neural network optimized by the crested porcupine optimizer and adaptive moment estimation (CPOA-RBFNN). By integrating the global search capability of swarm intelligence with the adaptive characteristics of gradient based optimization, the proposed method enhances both imaging accuracy and robustness. A total of 23 000 simulated datasets of pediatric pneumonia were constructed for training and testing. The proposed method was compared with Tikhonov regularization and the conventional radial basis function neural network (RBFNN), and evaluated using root mean square error (RMSE), image correlation coefficient (ICC), structural similarity index (SSIM), and peak signal-to-noise ratio (PSNR). Results show that under a noise level of 50 dB, the proposed method achieves the lowest RMSE (0.098), the highest ICC (0.922), and relatively high SSIM (0.909) and PSNR (9.295). Further clinical validation demonstrates that CPOA-RBFNN provides superior structural fidelity and lesion distinguishability in pneumonia reconstruction. In conclusion, the proposed method offers an effective solution for non-invasive, high-precision imaging and bedside-assisted diagnosis of pediatric pneumonia.","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 3","pages":"589-597"},"PeriodicalIF":0.0,"publicationDate":"2026-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13311061/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148346801","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

[Colorectal cancer diagnosis method based on dynamic gland-aware and tissue soft-clustering]. 基于动态腺体感知和组织软聚类的结直肠癌诊断方法。

生物医学工程学杂志 Pub Date : 2026-06-25 DOI: 10.7507/1001-5515.202603029

Shuzhi Su, Kexue Zhang, Yanmin Zhu, Xiaoni Zhong, Liu Xiang, Yong Dai

{"title":"[Colorectal cancer diagnosis method based on dynamic gland-aware and tissue soft-clustering].","authors":"Shuzhi Su, Kexue Zhang, Yanmin Zhu, Xiaoni Zhong, Liu Xiang, Yong Dai","doi":"10.7507/1001-5515.202603029","DOIUrl":"10.7507/1001-5515.202603029","url":null,"abstract":"In colorectal cancer histopathology, the collaborative perception of microscopic and salient lesions is critical for effective diagnosis and improved patient prognosis. However, existing deep learning methods struggle to simultaneously capture microscopic glandular disorganization and salient tissue lesions. To address this limitation, a colorectal cancer diagnosis network based on dynamic gland-aware and tissue soft-clustering (DGTSNet) is proposed. The method employs dynamic gland-aware convolution to explicitly perceive gland boundaries and dynamically adjust sampling offsets, while incorporating a continuous-domain constraint to prevent out-of-bound sampling, thereby enhancing the perception of microscopic glandular disorders. Meanwhile, a tissue soft-clustering module is utilized to adaptively generate clustering prototypes and guide pixels toward relevant prototype centroids according to semantic similarity, suppressing irrelevant background interference and enhancing responses to significant tissue lesions. Finally, a cascaded sparse coupling module is introduced to collaboratively modulate cross-semantic feature representations along both the spatial and channel dimensions, while constructing differentiable masks to suppress low-contribution semantics, thereby achieving collaborative coupling of cross-semantic features. Experimental results demonstrated that the proposed method achieved superior performance on the Chaoyang, Kather-5K, and EBHI datasets, as well as a real-world clinical validation cohort, outperforming multiple baseline models. The study shows that the proposed method can effectively enhance the joint perception of microscopic glandular disorders and significant tissue lesions, providing an effective solution for colorectal cancer diagnosis.","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 3","pages":"450-460"},"PeriodicalIF":0.0,"publicationDate":"2026-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13311055/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148346520","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

[Self-supervised classification method for breast pathology images fusing geometric priors and multi-scale attention]. [融合几何先验和多尺度关注的乳腺病理图像自监督分类方法]。

生物医学工程学杂志 Pub Date : 2026-06-25 DOI: 10.7507/1001-5515.202511059

Liang Jiang, Hui Cao, Yongqi Nie, Cheng Zhang

{"title":"[Self-supervised classification method for breast pathology images fusing geometric priors and multi-scale attention].","authors":"Liang Jiang, Hui Cao, Yongqi Nie, Cheng Zhang","doi":"10.7507/1001-5515.202511059","DOIUrl":"10.7507/1001-5515.202511059","url":null,"abstract":"Breast whole slide image (WSI) serves as an essential basis for breast cancer diagnosis and subtype classification. However, its high resolution, multi-scale structural characteristics, and arbitrary orientation pose substantial challenges for automated analysis. Existing deep learning methods typically rely on large amounts of annotated data and struggle to handle the rotational variability and scale differences inherent in pathological images, which limits their generalization ability in cross-center settings. To address these issues, this study proposes a self-supervised learning model, IAM-BYOL, which incorporated geometric priors into the representation learning process. Building upon the BYOL framework, the model introduced an isotropic attention module (IAM). By employing discrete rotation group convolution, IAM enabled weight sharing across different rotated versions of the convolutional kernels, endowing the encoder with structural rotation equivariance. A subsequent group pooling operation converted the equivariant features into rotation-invariant isotropic representations. In addition, a multi-scale attention mechanism adjusted feature weights adaptively according to responses from different receptive fields, allowing the model to capture informative patterns ranging from nuclear-level details to tissue-level organization. Experimental results demonstrated that IAM-BYOL achieved classification accuracies of 98.74%, 99.04%, 99.01%, and 98.63% on the BreakHis dataset at 40×, 100×, 200×, and 400× magnifications, respectively, while attaining an accuracy of 93.02% on the cross-center private clinical dataset BCD. These findings indicate that introducing geometric inductive biases into pathological image representation learning can effectively enhance model robustness and generalization capability.","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 3","pages":"471-478"},"PeriodicalIF":0.0,"publicationDate":"2026-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13311058/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148346809","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

[Mechanisms and applications of magnesium ion-regulated stem cell functions in promoting tendon-bone interface healing]. [镁离子调控的干细胞功能促进肌腱-骨界面愈合的机制和应用]。

生物医学工程学杂志 Pub Date : 2026-06-25 DOI: 10.7507/1001-5515.202512004

Xinke Zhu, Hao Yue, Xianghui Dong, Zhengchao Gao, Ming Ling, Zhengming Sun

{"title":"[Mechanisms and applications of magnesium ion-regulated stem cell functions in promoting tendon-bone interface healing].","authors":"Xinke Zhu, Hao Yue, Xianghui Dong, Zhengchao Gao, Ming Ling, Zhengming Sun","doi":"10.7507/1001-5515.202512004","DOIUrl":"10.7507/1001-5515.202512004","url":null,"abstract":"This review systematically examines the mechanisms and recent research progress of magnesium ions in promoting tendon-bone interface repair by regulating stem cell functions. Firstly, the analysis indicates that magnesium ions synergistically regulate stem cell proliferation, migration, and multidirectional differentiation through multiple signaling pathways, while simultaneously promoting angiogenesis and optimizing the immune microenvironment. Subsequently, a summary of existing research findings confirms that magnesium-based biodegradable biomaterials demonstrate favorable tissue repair-promoting effects in animal experiments. Finally, this article proposes that, given the spatiotemporal sequential characteristics of magnesium ion regulation on stem cells and the healing microenvironment, future research should focus on developing novel smart materials capable of precisely controlling magnesium ion release to match the healing process, thereby advancing its clinical translation and precision medicine applications in the field of tendon-bone repair.","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 3","pages":"654-660"},"PeriodicalIF":0.0,"publicationDate":"2026-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13311030/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148346711","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

[Research progress on the neuromodulation targets in stroke rehabilitation]. 脑卒中康复中神经调节靶点的研究进展

生物医学工程学杂志 Pub Date : 2026-06-25 DOI: 10.7507/1001-5515.202509066

Xuedong Yang, Ling Wang, Jiajia Yang, Chenguang Zheng, Dong Ming

引用次数: 0

[Application and perspective of novel auditory intervention paradigms based on verbal and nonverbal stimuli for severe traumatic brain injury]. [基于言语和非言语刺激的新型听觉干预范式在重型颅脑损伤中的应用与展望]。

生物医学工程学杂志 Pub Date : 2026-06-25 DOI: 10.7507/1001-5515.202601035

Xulong Li, Yuzhe Yuan, Peng Chen, Zhiyong Liu, Kang Li, Haibo Teng

{"title":"[Application and perspective of novel auditory intervention paradigms based on verbal and nonverbal stimuli for severe traumatic brain injury].","authors":"Xulong Li, Yuzhe Yuan, Peng Chen, Zhiyong Liu, Kang Li, Haibo Teng","doi":"10.7507/1001-5515.202601035","DOIUrl":"10.7507/1001-5515.202601035","url":null,"abstract":"Patients with severe traumatic brain injury (TBI) often experience disorders of consciousness (DoC) and motor impairments, which pose challenges to the implementation of conventional intervention approaches. As one of the relatively preserved sensory pathways in these patients, the auditory system holds considerable potential for assessing consciousness and facilitating its recovery. Therefore, this review systematically examines the mechanisms of verbal and nonverbal stimuli in consciousness recovery, focusing on analyzing the synergistic effects and limitations of language stimuli in emotional arousal and semantic integration. Based on this, a complementary mechanism leveraging the respective strengths of both approaches has been explored to establish a new intervention paradigm. Furthermore, integrating advancements in brain-computer interface (BCI) technology, it proposes a closed-loop intervention approach that combines multi-type auditory stimuli with real-time neural feedback. This framework emphasizes individual differences and dynamic regulation, providing theoretical foundations and developmental directions for constructing precision-oriented, mechanism-driven auditory intervention paradigms for severe TBI.","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 3","pages":"625-632"},"PeriodicalIF":0.0,"publicationDate":"2026-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13311039/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148346599","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

[Research progress on three-dimensional finite element analysis for fixed implant restoration of edentulous jaw]. [无牙颌固定种植体修复三维有限元分析研究进展]。

生物医学工程学杂志 Pub Date : 2026-04-25 DOI: 10.7507/1001-5515.202504001

Yue Lan, Baohui Su

{"title":"[Research progress on three-dimensional finite element analysis for fixed implant restoration of edentulous jaw].","authors":"Yue Lan, Baohui Su","doi":"10.7507/1001-5515.202504001","DOIUrl":"10.7507/1001-5515.202504001","url":null,"abstract":"With the intensification of population aging, the number of edentulous patients continues rising. Fixed implant prostheses have become the primary treatment for tooth loss due to their superior chewing efficiency and comfort. However, improper implant prosthetic design may lead to various mechanical and biological complications, and even result in implant failure. Therefore, systematically analyzing the mechanical factors that influence the outcomes of implant restoration and optimizing the design hold significant clinical importance. Finite element analysis, as an effective biomechanical research tool, can simulate the stress distribution in dental implants and bone tissues under different loading conditions, thereby providing a theoretical basis for optimizing implant restoration plans. This review focuses on the impact of factors including implant number, size, shape, inclination angle, framework design and different modeling assumptions on the stress distribution in edentulous implant, aiming to provide references for developing clinically rational implant restoration plans.","PeriodicalId":39324,"journal":{"name":"生物医学工程学杂志","volume":"43 2","pages":"434-440"},"PeriodicalIF":0.0,"publicationDate":"2026-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13112213/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147784301","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