摘要
宫颈癌是女性最常见的恶性肿瘤之一,其发病率及死亡率较高,且发病呈年轻化趋势。早期诊断和预测可以大大改善宫颈癌的治疗效果。深度学习和影像组学是目前影像领域的研究热点,已逐步应用于宫颈癌筛查、诊断、鉴别诊断、疗效评估及预后预测等。本文就深度学习和影像组学在宫颈癌中的研究进展进行综述。
Cervical cancer is one of the most common malignant tumors in women,with high morbidity and mortality,and shows a younger trend.Early diagnosis and prediction will greatly improve the therapeutic effect.Deep learning and Radiomics are the focus of research in the radiology field,which are gradually applied to cervical cancer screening,diagnosis,differential diagnosis,curative effect evaluation and prognosis prediction.This article reviews the research progress of deep learning and radiomics in cervical cancer.
作者
郭城
辛仲宏
王敏哲
郑悠
雷军强
GUO Cheng;XIN Zhonghong;WANG Minzhe;ZHENG You;LEI Junqiang(Department of Radiology,the First Hospital of Lanzhou University,Lanzhou 730000,China;不详)
出处
《中国医学影像学杂志》
CSCD
北大核心
2021年第12期1251-1255,共5页
Chinese Journal of Medical Imaging
基金
甘肃省自然科学基金(20JR10RA684)。
关键词
宫颈肿瘤
体层摄影术
X线计算机
磁共振成像
深度学习
影像组学
淋巴转移
诊断
鉴别
综述
Uterine cervical neoplasms
Tomography,X-ray computed
Magnetic resonance imaging
Deep learning
Radiomics
Lymphatic metastasis
Diagnosis,differential
Review
