• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

Radiomics and Computerized Analysis of CT Images: Looking Forward.

作者信息

Elicker Brett M, Sohn Jae Ho

机构信息

Department of Radiology and Biomedical Imaging, University of California, San Francisco, Box 0628, San Francisco, CA 94143.

出版信息

Radiol Cardiothorac Imaging. 2020 Dec 17;2(6):e200589. doi: 10.1148/ryct.2020200589. eCollection 2020 Dec.

DOI:10.1148/ryct.2020200589
PMID:33779641
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7977988/
Abstract
摘要

相似文献

1
Radiomics and Computerized Analysis of CT Images: Looking Forward.CT图像的放射组学与计算机分析:展望未来。
Radiol Cardiothorac Imaging. 2020 Dec 17;2(6):e200589. doi: 10.1148/ryct.2020200589. eCollection 2020 Dec.
2
A multidomain fusion model of radiomics and deep learning to discriminate between PDAC and AIP based on F-FDG PET/CT images.基于 F-FDG PET/CT 图像的放射组学和深度学习的多域融合模型用于鉴别 PDAC 和 AIP。
Jpn J Radiol. 2023 Apr;41(4):417-427. doi: 10.1007/s11604-022-01363-1. Epub 2022 Nov 21.
3
Radiomics analysis of contrast-enhanced computerized tomography for differentiation of gastric schwannomas from gastric gastrointestinal stromal tumors.基于对比增强 CT 的影像组学分析鉴别胃 schwann 瘤与胃胃肠间质瘤。
J Cancer Res Clin Oncol. 2024 Feb 9;150(2):87. doi: 10.1007/s00432-023-05545-w.
4
Potential feature exploration and model development based on 18F-FDG PET/CT images for differentiating benign and malignant lung lesions.基于 18F-FDG PET/CT 图像的良恶性肺病变鉴别中潜在特征的探索和模型开发。
Eur J Radiol. 2019 Dec;121:108735. doi: 10.1016/j.ejrad.2019.108735. Epub 2019 Nov 6.
5
Robustness of radiomics features of virtual unenhanced and virtual monoenergetic images in dual-energy CT among different imaging platforms and potential role of CT number variability.不同成像平台双能量CT中虚拟平扫及虚拟单能量图像的影像组学特征稳健性及CT值变异性的潜在作用
Insights Imaging. 2023 May 11;14(1):79. doi: 10.1186/s13244-023-01426-5.
6
Comparison of deep-learning and radiomics-based machine-learning methods for the identification of chronic obstructive pulmonary disease on low-dose computed tomography images.基于深度学习和放射组学的机器学习方法在低剂量计算机断层扫描图像上识别慢性阻塞性肺疾病的比较。
Quant Imaging Med Surg. 2024 Mar 15;14(3):2485-2498. doi: 10.21037/qims-23-1307. Epub 2024 Mar 5.
7
Preoperative prediction of malignant potential of 2-5 cm gastric gastrointestinal stromal tumors by computerized tomography-based radiomics.基于计算机断层扫描的放射组学对2-5厘米胃胃肠道间质瘤恶性潜能的术前预测
World J Gastrointest Oncol. 2022 May 15;14(5):1014-1026. doi: 10.4251/wjgo.v14.i5.1014.
8
The impact of respiratory motion and CT pitch on the robustness of radiomics feature extraction in 4DCT lung imaging.在 4DCT 肺部成像中,呼吸运动和 CT 螺距对放射组学特征提取稳健性的影响。
Comput Methods Programs Biomed. 2020 Dec;197:105719. doi: 10.1016/j.cmpb.2020.105719. Epub 2020 Aug 27.
9
Application of 18F-FDG PET-CT Images Based Radiomics in Identifying Vertebral Multiple Myeloma and Bone Metastases.基于18F-FDG PET-CT图像的影像组学在鉴别椎体多发性骨髓瘤和骨转移瘤中的应用
Front Med (Lausanne). 2022 Apr 18;9:874847. doi: 10.3389/fmed.2022.874847. eCollection 2022.
10
Synthesis of virtual monoenergetic images from kilovoltage peak images using wavelet loss enhanced CycleGAN for improving radiomics features reproducibility.使用小波损失增强循环生成对抗网络从千伏峰值图像合成虚拟单能图像以提高放射组学特征的可重复性
Quant Imaging Med Surg. 2024 Mar 15;14(3):2370-2390. doi: 10.21037/qims-23-922. Epub 2024 Mar 7.

引用本文的文献

1
Predicting abnormal epicardial adipose tissue in psoriasis patients by integrating radiomics from non-contrast chest CT with serological biomarkers.通过整合非增强胸部CT的放射组学特征与血清生物标志物预测银屑病患者的心外膜脂肪组织异常
BMC Med Imaging. 2025 Jul 1;25(1):240. doi: 10.1186/s12880-025-01755-5.
2
Clinical Variables and Radiomics Features for Predicting Pneumothorax in Patients Undergoing CT-guided Transthoracic Core Needle Biopsy.用于预测 CT 引导经胸核心针活检患者气胸的临床变量和放射组学特征。
Radiol Cardiothorac Imaging. 2024 Jun;6(3):e230278. doi: 10.1148/ryct.230278.
3
A nomogram based on radiomics intermuscular adipose analysis to indicate arteriosclerosis in patients with newly diagnosed type 2 diabetes.基于影像组学肌间脂肪分析的列线图,用于预测新诊断 2 型糖尿病患者的动脉硬化。
Front Endocrinol (Lausanne). 2023 May 26;14:1201110. doi: 10.3389/fendo.2023.1201110. eCollection 2023.

本文引用的文献

1
Quantification of Cystic Fibrosis Lung Disease with Radiomics-based CT Scores.基于影像组学的CT评分对囊性纤维化肺病的量化分析
Radiol Cardiothorac Imaging. 2020 Dec 17;2(6):e200022. doi: 10.1148/ryct.2020200022. eCollection 2020 Dec.
2
Evolving the pulmonary nodules diagnosis from classical approaches to deep learning-aided decision support: three decades' development course and future prospect.从经典方法到深度学习辅助决策支持的肺部结节诊断演进:三十年的发展历程和未来展望。
J Cancer Res Clin Oncol. 2020 Jan;146(1):153-185. doi: 10.1007/s00432-019-03098-5. Epub 2019 Nov 30.
3
Longitudinal prediction of outcome in idiopathic pulmonary fibrosis using automated CT analysis.应用 CT 分析自动化技术对特发性肺纤维化患者的结局进行纵向预测。
Eur Respir J. 2019 Sep 30;54(3). doi: 10.1183/13993003.02341-2018. Print 2019 Sep.
4
CT densitometry in emphysema: a systematic review of its clinical utility.肺气肿的CT密度测定法:对其临床效用的系统评价
Int J Chron Obstruct Pulmon Dis. 2018 Feb 7;13:547-563. doi: 10.2147/COPD.S143066. eCollection 2018.
5
A 3-year prognostic score for adults with cystic fibrosis.成人囊性纤维化 3 年预后评分。
J Cyst Fibros. 2017 Nov;16(6):702-708. doi: 10.1016/j.jcf.2017.03.004. Epub 2017 Mar 18.
6
The CF-ABLE score: a novel clinical prediction rule for prognosis in patients with cystic fibrosis.CF-ABLE 评分:一种用于预测囊性纤维化患者预后的新型临床预测规则。
Chest. 2013 May;143(5):1358-1364. doi: 10.1378/chest.12-2022.
7
Predictive 5-year survivorship model of cystic fibrosis.囊性纤维化的5年预测生存模型。
Am J Epidemiol. 2001 Feb 15;153(4):345-52. doi: 10.1093/aje/153.4.345.
8
Comparison of the clinical manifestations of cystic fibrosis in black and white patients.黑人和白人囊性纤维化患者临床表现的比较。
J Pediatr. 1998 Feb;132(2):255-9. doi: 10.1016/s0022-3476(98)70441-x.