期刊名：Bioengineering

期刊主页：https://www.mdpi.com/journal/bioengineering

近年来，人工智能与先进工程技术的深度融合正推动医学超声领域从图像优化向智能化诊疗全面跨越。本专题精选发表于 Bioengineering 的系列研究，涵盖深度学习在多器官检测（甲状腺、乳腺、肺部）、移动诊疗架构评估、超声物理模型仿真、组织仿体材料开发及自动化辅助测量等前沿方向，系统展示了超声技术在精准诊断、治疗规划与生物医学工程交叉领域的最新突破。

1. A Multi-View Deep Learning Model for Thyroid Nodules Detection and Characterization in Ultrasound Imaging

一种用于超声成像中甲状腺结节检测与特征分析的多视角深度学习模型

文章链接：https://www.mdpi.com/2306-5354/11/7/648

MDPI引用格式: Vahdati, S.; Khosravi, B.; Robinson, K.A.; Rouzrokh, P.; Moassefi, M.; Akkus, Z.; Erickson, B.J. A Multi-View Deep Learning Model for Thyroid Nodules Detection and Characterization in Ultrasound Imaging. Bioengineering 2024, 11, 648.

2. Evaluation of Deep Learning Model Architectures for Point-of-Care Ultrasound Diagnostics

移动诊疗超声诊断的深度学习模型架构评估

文章链接：https://www.mdpi.com/2306-5354/11/4/392

MDPI引用格式: Hernandez Torres, S.I.; Ruiz, A.; Holland, L.; Ortiz, R.; Snider, E.J. Evaluation of Deep Learning Model Architectures for Point-of-Care Ultrasound Diagnostics. Bioengineering 2024, 11, 392.

3. Estimation of Validity of A-Mode Ultrasound for Measurements of Muscle Thickness and Muscle Quality

A型超声测量肌肉厚度与肌肉质量的效度评估

文章链接：https://www.mdpi.com/2306-5354/11/2/149

MDPI引用格式: Lee, J.-W.; Hong, S.-U.; Lee, J.-H.; Park, S.-Y. Estimation of Validity of A-Mode Ultrasound for Measurements of Muscle Thickness and Muscle Quality. Bioengineering 2024, 11, 149.

4. The Role of Treatment-Related Parameters and Brain Morphology in the Lesion Volume of Magnetic-Resonance-Guided Focused Ultrasound Thalamotomy in Patients with Tremor-Dominant Neurological Conditions

治疗相关参数与脑部形态在磁共振引导聚焦超声丘脑切开术治疗震颤优势型神经系统疾病中病灶体积的作用

文章链接：https://www.mdpi.com/2306-5354/11/4/373

MDPI引用格式: Morabito, R.; Cammaroto, S.; Militi, A.; Smorto, C.; Anfuso, C.; Lavano, A.; Tomasello, F.; Di Lorenzo, G.; Brigandì, A.; Sorbera, C.; et al. The Role of Treatment-Related Parameters and Brain Morphology in the Lesion Volume of Magnetic-Resonance-Guided Focused Ultrasound Thalamotomy in Patients with Tremor-Dominant Neurological Conditions. Bioengineering 2024, 11, 373.

5. Experimental Validation of Time-Explicit Ultrasound Propagation Models with Sound Diffusivity or Viscous Attenuation in Biological Tissues Using COMSOL Multiphysics

利用COMSOL Multiphysics对生物组织中含声扩散性或粘性衰减的显式时间超声传播模型进行实验验证

文章链接：https://www.mdpi.com/2306-5354/12/9/946

MDPI引用格式: Fernandes, N.A.T.C.; Sharma, S.; Arieira, A.; Hinckel, B.; Silva, F.; Leal, A.; Carvalho, Ó. Experimental Validation of Time-Explicit Ultrasound Propagation Models with Sound Diffusivity or Viscous Attenuation in Biological Tissues Using COMSOL Multiphysics. Bioengineering 2025, 12, 946.

6. Evaluation of Denoising Performance of ResNet Deep Learning Model for Ultrasound Images Corresponding to Two Frequency Parameters

基于双频参数超声图像的ResNet深度学习模型去噪性能评估

文章链接：https://www.mdpi.com/2306-5354/11/7/723

MDPI引用格式: Kang, H.; Park, C.; Yang, H. Evaluation of Denoising Performance of ResNet Deep Learning Model for Ultrasound Images Corresponding to Two Frequency Parameters. Bioengineering 2024, 11, 723.

7. Improved A-Line and B-Line Detection in Lung Ultrasound Using Deep Learning with Boundary-Aware Dice Loss

使用边界感知Dice损失的深度学习技术改进肺部超声A线和B线检测

文章链接：https://www.mdpi.com/2306-5354/12/3/311

MDPI引用格式: Abbasi, S.; Wahd, A.S.; Ghosh, S.; Ezzelarab, M.; Panicker, M.; Chen, Y.T.; Jaremko, J.L.; Hareendranathan, A. Improved A-Line and B-Line Detection in Lung Ultrasound Using Deep Learning with Boundary-Aware Dice Loss. Bioengineering 2025, 12, 311.

8. AI-Enhanced 3D Transperineal Ultrasound: Advancing Biometric Measurements for Precise Prolapse Severity Assessment

AI增强三维经会阴超声：推进生物测量学技术，实现盆腔器官脱垂严重程度的精准评估

文章链接：https://www.mdpi.com/2306-5354/12/7/754

MDPI引用格式: De Vicari, D.; Barba, M.; Cola, A.; Costa, C.; Palucci, M.; Frigerio, M. AI-Enhanced 3D Transperineal Ultrasound: Advancing Biometric Measurements for Precise Prolapse Severity Assessment. Bioengineering 2025, 12, 754.

9. Tissue-Mimicking Material Fabrication and Properties for Multiparametric Ultrasound Phantoms: A Systematic Review

面向多参数超声体模的组织仿生材料制备与性能研究：系统性综述

文章链接：https://www.mdpi.com/2306-5354/11/6/620

MDPI引用格式: Jawli, A.; Aldehani, W.; Nabi, G.; Huang, Z. Tissue-Mimicking Material Fabrication and Properties for Multiparametric Ultrasound Phantoms: A Systematic Review. Bioengineering 2024, 11, 620.

10. Explainable DCNN Decision Framework for Breast Lesion Classification from Ultrasound Images Based on Cancer Characteristics

基于癌症特征的超声图像乳腺病变可解释深度卷积神经网络决策框架

文章链接：https://www.mdpi.com/2306-5354/11/5/453

MDPI引用格式: AlZoubi, A.; Eskandari, A.; Yu, H.; Du, H. Explainable DCNN Decision Framework for Breast Lesion Classification from Ultrasound Images Based on Cancer Characteristics. Bioengineering 2024, 11, 453.

11. Artificial Intelligence in the Diagnostic Use of Transcranial Doppler and Sonography: A Scoping Review of Current Applications and Future Directions

人工智能在经颅多普勒与超声诊断中的应用：当前实践与未来方向的范围综述

文章链接：https://www.mdpi.com/2306-5354/12/7/681

MDPI引用格式: Miceli, G.; Basso, M.G.; Cocciola, E.; Tuttolomondo, A., on behalf of the Italian Society of Neurosonology and Cerebral Hemodynamics (SINSEC) and SINSEC Study Group for Artificial Intelligence in Neurosonology. Artificial Intelligence in the Diagnostic Use of Transcranial Doppler and Sonography: A Scoping Review of Current Applications and Future Directions. Bioengineering 2025, 12, 681.

12. Using AI Segmentation Models to Improve Foreign Body Detection and Triage from Ultrasound Images

使用AI分割模型优化超声图像异物检测与临床分诊

文章链接：https://www.mdpi.com/2306-5354/11/2/128

MDPI引用格式: Holland, L.; Hernandez Torres, S.I.; Snider, E.J. Using AI Segmentation Models to Improve Foreign Body Detection and Triage from Ultrasound Images. Bioengineering 2024, 11, 128.

13. Evaluation of a Semi-Automated Ultrasound Guidance System for Central Vascular Access

中央血管通路半自动化超声引导系统的效能评估

文章链接：https://www.mdpi.com/2306-5354/11/12/1271

MDPI引用格式: Hernandez Torres, S.I.; Caldwell, N.W.; Snider, E.J. Evaluation of a Semi-Automated Ultrasound Guidance System for Central Vascular Access. Bioengineering 2024, 11, 1271.

14. The Efficacy of Semantics-Preserving Transformations in Self-Supervised Learning for Medical Ultrasound

医学超声自监督学习中，语义保持变换的效能研究

文章链接：https://www.mdpi.com/2306-5354/12/8/855

MDPI引用格式: VanBerlo, B.; Hoey, J.; Wong, A.; Arntfield, R. The Efficacy of Semantics-Preserving Transformations in Self-Supervised Learning for Medical Ultrasound. Bioengineering 2025, 12, 855.

15. Evaluation of Operator Variability and Validation of an AI-Assisted α-Angle Measurement System for DDH Using a Phantom Model

基于体模的人工智能辅助DDH α角测量系统的操作者差异性评估与效能验证

文章链接：https://www.mdpi.com/2306-5354/12/9/1004

MDPI引用格式: Ohashi, Y.; Shimizu, T.; Koyano, H.; Nakamura, Y.; Takahashi, D.; Yamada, K.; Iwasaki, N. Evaluation of Operator Variability and Validation of an AI-Assisted α-Angle Measurement System for DDH Using a Phantom Model. Bioengineering 2025, 12, 1004.

Bioengineering 期刊介绍

主编：Anthony Guiseppi-Elie, Anderson University, USA

主要发表生物医学工程及应用，生物过程和生物系统工程与应用，生物分子、细胞和组织工程及应用，以及生化工程与应用等相关领域的最新科学技术及应用。期刊已被PubMed、Scopus、SCIE (Web of Science) 等数据库收录。

2022 Impact Factor：4.6

2023 CiteScore：4.0

Time to First Decison：17.7 Days

Acceptance to Publication：3.6 Days