Advances in the application of non-contrast CT radiomics and machine learning in the diagnosis and treat-ment process of hypertensive Intracerebral hemorrhage

VernacularTitle:非对比剂CT影像组学和机器学习在高血压脑出血诊疗过程中应用研究进展
Author: Yanwen JIANG ¹ ; Hu QIN ; Zhaofu LENG ; Aikel-Amu PAZILIYA ; Yongxin WANG
Author Information

1. 新疆医科大学第一附属医院神经外科(乌鲁木齐 830054)
Keywords: Hypertensive intracerebral hemorrhage; Radiomics; Machine learning; Image features; Deep learn-ing; Algorithm
From: Chinese Journal of Nervous and Mental Diseases 2023;49(10):609-614
CountryChina
Language:Chinese
Abstract: Hypertensive intracerebral hemorrhage(HICH)is a disease with a rapid onset,rapid progression,high mortality rate,and long-term impact on the ability to function.Non-contrast agent-based CT(NCCT)is a common method for evaluating and identifying HICH.Recent radiomics in image processing and machine learning(ML)have enabled the extraction of high-dimensional feature information from medical images,which can be used to rapidly and accurately diagnose HICH and predict its course of disease.The paper describes the application of radiomics and ML techniques in HICH diagnosis and treatment,and identifies possible directions for future research.