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作 者:李翻翻 周静 马晓丽 余有珍[1,2] 何文惠 王婷 王小兰 罗娜[1,2] 马国婧 王敏 马敏杰 Li Fanfan;Zhou Jing;Ma Xiaoli;Yu Youzhen;He Wenhui;Wang Ting;Wang Xiaolan;Luo Na;Ma Guojing;Wang Min;Ma Minjie(School of Nursing,Gansu University of Chinese Medicine,Lanzhou 730000,China;Department of Thoracic Surgery,The First Hospital of Lanzhou University,Lanzhou 730000,China;Key Technology Development and Application of Thoracic Surgery Specialty Gansu Province International Science and Technology Cooperation Base,The First Hospital of Lanzhou University,Lanzhou 730000,China;Medical Quality Control Center of Thoracic Surgery in Gansu Province,The First Hospital of Lanzhou University,Lanzhou 730000,China;Department of Clinical Medicine,Chinese People's Liberation Army Unit 68302 Hospital,Weinan 714000,Shaanxi,China)
机构地区:[1]甘肃中医药大学护理学院,甘肃兰州730000 [2]兰州大学第一医院胸外科,甘肃兰州730000 [3]兰州大学第一医院胸外科关键技术与应用甘肃省国际合作基地,甘肃兰州730000 [4]兰州大学第一医院甘肃省胸外科医疗质量控制中心,甘肃兰州730000 [5]中国人民解放军68302部队医院临床医学科,陕西渭南714000
出 处:《兰州大学学报(医学版)》2024年第3期81-86,共6页Journal of Lanzhou University(Medical Sciences)
基 金:甘肃省自然科学基金资助项目(21JR1RA092);甘肃中医药大学研究生创新基金资助项目(2022CX79)。
摘 要:随着人工智能与物联网等数字技术的不断纵深发展,以伤口评估和管理为主的新兴技术和模式智能迭进,数字化伤口成像已在糖尿病足、静脉溃疡及手术伤口评估等领域取得一些研究成果。基于人工智能的图像识别和分割系统已实现便捷、即时及精准的伤口评估,并集成伤口治疗决策支持系统。一些新兴设备已应用人工智能实现伤口结构和组织成分的精准显像,形成伤口自动化三维测量及可视化的组织颜色分区,其中,基于近红外和热光谱等的光学成像设备增强了传统的视觉评估。基于人工智能的机器学习或深度学习技术将融合多种图像模式,以提供精准可靠的伤口治疗决策支持体系,加速愈合进程与患者康复。With the continuous and deep development of digital technologies such as artificial intelligence and the Internet,technologies and modes focusing on wound assessment and management have also made intelligent iterations,and digital wound imaging has achieved certain research results in the fields of diabetic foot,venous ulcer,and surgical wound assessment.Artificial intelligence-based image recognition and segmentation systems have enabled convenient,immediate and accurate wound assessment and integrated wound treatment decision support systems.Furthermore,several emerging devices have also applied artificial intelligence to achieve accurate visualization of wound structure and tissue composition,resulting in automated three-dimensional measurement of wounds and visual tissue color partitioning,where optical imaging devices based on near-infrared and thermal spectroscopy,among others,have augmented the traditional visual assessment.In the future,machine learning or deep learning techniques based on artificial intelligence technologies will incorporate multiple image modalities to provide an accurate and reliable decision support system for wound treatment, thus accelerating the healing process and patient recovery.
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