Research progresses of deep learning based on non-contrast CT in spontaneous intracerebral hemorrhage

VernacularTitle:平扫CT深度学习用于自发性脑出血研究进展
Author: Yu ZHOU ¹ ; Weijia ZHONG ¹ ; Tianxing HUANG ¹ ; Wenjie LI ¹ ; Zhiming ZHOU ¹
Author Information

1. 重庆医科大学附属第二医院放射科,重庆 400010
Publication Type:Journal Article
Keywords: cerebral hemorrhage; hematoma; tomography,X-ray computed; deep learning
From: Chinese Journal of Medical Imaging Technology 2024;40(12):1945-1948
CountryChina
Language:Chinese
Abstract: Spontaneous intracerebral hemorrhage(sICH)refers to non-traumatic bleeding within brain parenchyma,presenting as a neurological emergency with high disability rate and mortality.Early diagnosis and treatment sICH are important to improve prognosis.Non-contrast CT(NCT)is a primary imaging modality for diagnosing intracerebral hemorrhage.In recent years,deep learning(DL)had shown unparalleled potential in automatic detection of cerebral hemorrhage,segmentation and calculation of hematoma volume,identification of edema around hematoma,etc,being able to assist doctors in diagnosis and treatment of sICH for reducing mortality and improving patients'life quality.The research progresses of DL based on NCT in sICH were reviewed in this article.