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作 者:李卓远 徐国豪 王峻晨 王赛硕 王传涛 翟吉良[2] LI Zhuoyuan;XU Guohao;WANG Junchen;WANG Saishuo;WANG Chuantao;ZHAI Jiliang(School of Electromechanical and Vehicle Engineering,Beijing University of Civil Engineering and Architecture,Beijing 102616,China;Department of Orthopaedics,Peking Union Medical College Hospital,Chinese Academy of Medical Sciences&Peking Union Medical College,Beijing 100730,China)
机构地区:[1]北京建筑大学机电与车辆工程学院,北京102616 [2]中国医学科学院北京协和医院骨科,北京100730
出 处:《协和医学杂志》2023年第6期1162-1169,共8页Medical Journal of Peking Union Medical College Hospital
基 金:中国医学科学院医学与健康科技创新工程(2022-I2M-C&T-B-035);中央高水平医院临床科研专项(2022-PUMCH-A-121)。
摘 要:单一模态的医学影像所包含的疾病特征信息有限,临床医生可通过综合分析多种模态的医学影像信息以明确诊断,但由于医疗资源及诊疗时间受限,医生一般无法在短时间内获得所需的多模态影像信息。跨模态医学影像重建技术能够生成临床所需的多种模态医学影像,有望辅助临床医生对疾病进行精准诊疗。目前,传统跨模态重建技术已实现部分临床场景的应用,但重建影像的生成质量有待进一步提高,生成对抗网络可重建出临床所需的高质量多模态医学影像,最大程度地节约医疗资源并缩短患者就诊时间。本文就生成对抗网络在X线、CT、MRI、PET等多模态影像之间的跨模态重建应用研究作一综述,以期为开发更先进的跨模态重建技术提供借鉴。Single-modal medical images contain limited disease-specific information.To analyze and di-agnose patients,clinicians often need to integrate multiple modal images.However,due to limited medical re-sources and treatment time,it may be difficult to obtain multi-modal images.Cross-modal image reconstruction can generate medical images for clinical needs,thus assisting clinicians in accurately diagnosing and treating diseases.Traditional cross-modal reconstruction techniques have been applied in some clinical scenarios,but the quality of the reconstructed images needs further improvement.Generative adversarial network(GAN)can recover high-quality and complete image data from low-quality or incomplete medical image data,maximally savings medical equipment resources and accelerating medical treatment speed.This article summarizes the ap-plications of GAN technology in cross-modal image reconstruction across X-ray imaging,computed tomography imaging,magnetic resonance imaging,and positron emission tomography imaging,to provide reference for the development of more advanced cross-modal reconstruction techniques.
分 类 号:R445[医药卫生—影像医学与核医学] TP37[医药卫生—诊断学]
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