Artificial Intelligence in Head and Neck Imaging

被引:6
|
作者
Pham, Nancy [1 ,2 ]
Ju, Connie [2 ]
Kong, Tracie [2 ]
Mukherji, Suresh K. [2 ]
机构
[1] Univ Calif Los Angeles, David Geffen Sch Med, Radiol Dept, Neuroradiol, Los Angeles, CA 90095 USA
[2] Univ Illinois, Radiol Dept, Neuroradiol, Chicago, IL 60680 USA
关键词
SQUAMOUS-CELL CARCINOMA; FINE-NEEDLE-ASPIRATION; LYMPH-NODE METASTASES; CANCER; ULTRASONOGRAPHY; PREDICTION; MANAGEMENT; RADIOMICS; IMPROVE; LESIONS;
D O I
10.1053/j.sult.2022.02.006
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Artificial intelligence (AI) can be applied to head and neck imaging to augment image quality and various clinical tasks including segmentation of tumor volumes, tumor characterization, tumor prognostication and treatment response, and prediction of metastatic lymph node disease. Head and neck oncology care is well positioned for the application of AI since treatment is guided by a wealth of information derived from CT, MRI, and PET imaging data. AI-based methods can integrate complex imaging, histologic, molecular, and clinical data to model tumor biology and behavior, and potentially identify associations, far beyond what conventional qualitative imaging can provide alone. (C) 2022 Elsevier Inc. All rights reserved.
引用
收藏
页码:170 / 175
页数:6
相关论文
共 50 条