Advance of deep learning in diagnosis and treatment of&nbsp; <sup>18</sup> F-FDG PET/CT for lung cancer

LI Bingbing; WU Zhifang; YANG Shuai; CUI Caozhe; LI Xiaomeng; LYU Doudou; HU Lingzhi nbsp

doi:10.19732/j.cnki.2096-6210.2023.05.010

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Advance of deep learning in diagnosis and treatment of ¹⁸ F-FDG PET/CT for lung cancer

更新时间：2025-12-15

- Advance of deep learning in diagnosis and treatment of ¹⁸ F-FDG PET/CT for lung cancer
- Vol. 32, Issue 5, Pages: 461-465(2023)
- 作者机构：
  
  分子影像精准诊疗省部共建协同创新中心,太原,030001
- 作者简介：
- 基金信息：
- DOI：10.19732/j.cnki.2096-6210.2023.05.010
  CLC：
- Published Online：02 November 2023，
  
  Published：02 November 2023
- 稿件说明：
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李冰冰,武志芳,杨帅,等. 深度学习在肺癌¹⁸F-FDG PET/CT诊疗中的应用研究进展[J]. 肿瘤影像学, 2023, 32(5): 461-465 https://doi.

org/10.19732/j.cnki.2096-6210.2023.05.010
李冰冰,武志芳,杨帅,等. 深度学习在肺癌¹⁸F-FDG PET/CT诊疗中的应用研究进展[J]. 肿瘤影像学, 2023, 32(5): 461-465 https://doi. DOI： 10.19732/j.cnki.2096-6210.2023.05.010.

org/10.19732/j.cnki.2096-6210.2023.05.010 DOI：

摘要

肺癌是中国常见的恶性肿瘤，其发病率及死亡率均居癌症首位。由于早期症状不典型且缺乏有效的筛查手段，大多数肺癌患者发现时已处于晚期，预后较差。改善预后的关键在于早发现、早诊断、早治疗。随着人工智能和医疗大数据分析等前沿技术的不断进步，深度学习作为目前人工智能发展迅猛的一大分支，被认为是医学图像分析领域的宝贵工具，现已在早期肺癌的筛查、诊疗和预后评估以及晚期肺癌的随访中广泛应用，并取得诸多成果。本文阐述了近年来深度学习在肺癌 18 F-FDG 正电子发射体层成像（positron emission tomography，PET）/计算机体层成像（computed tomography，CT）诊疗中的应用现状及研究进展，主要介绍图像采集与重建、病灶检测与分割、诊断与鉴别诊断、基因突变状态与免疫治疗靶点及治疗反应与结局预测等，并对其发展前景及面临的挑战予以梳理。

Abstract

Lung cancer is the common malignant tumor in China

and its incidence and mortality rank first. Due to atypical early symptoms and lack of effective screening methods

most lung cancer patients are detected at an advanced stage and often lead to poor prognosis. The key factors for improving the prognosis of lung cancer patients are early detection

early diagnosis and early treatment. With the continuous progress of cutting-edge technologies such as artificial intelligence and medical big data analysis

Deep learning

as a major branch of artificial intelligence

is recognized as a valuable tool in the field of medical image analysis

and has been widely used in the screening and diagnosis of early-stage lung cancer

treatment decision-making

prediction of prognosis and follow-up of advanced lung cancer

and many results have been reported in previous literatures. This paper reviewed the development status of deep learning technology in the diagnosis and treatment of lung cancer 18 F-FDG PET/CT in recent years

covered the aspects of image acquisition and reconstruction

lesion detection and segmentation

diagnosis and differential diagnosis

gene mutation status and molecular therapeutic target prediction

treatment response and outcome prediction

and analyzed its development prospects and challenges.

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Advance of deep learning in diagnosis and treatment of 18 F-FDG PET/CT for lung cancer

DOI：10.19732/j.cnki.2096-6210.2023.05.010

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Advance of deep learning in diagnosis and treatment of ¹⁸ F-FDG PET/CT for lung cancer