Search research articles

关于 JoVE

概览领导团队博客 JoVE 帮助中心

作者

出版流程编辑委员会范围与政策同行评审常见问题投稿

图书馆员

用户评价订阅访问资源图书馆顾问委员会常见问题

研究

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments 存档

教育

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual 教师资源中心教师网站

使用条款与条件

相关概念视频

Brain Imaging

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans), magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序

Same author

STOPBANG versus NOSAS in screening patients with severe obstructive sleep apnea.

La Tunisie medicale·2026

Same author

La Tunisie medicale·2026

Same author

A knowledge-guided and uncertainty-calibrated multimodal framework for fracture diagnosis and radiology report generation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2026

Same author

Efficacy and safety of two protocols of intravenous insulin therapy in the management of diabetic ketoacidosis.

La Tunisie medicale·2023

Same author

Intelligent Recommendations of Startup Projects in Smart Cities and Smart Health Using Social Media Mining.

Journal of healthcare engineering·2021

Same author

Base Excess usefulness for prediction of immediate mortality in severe trauma patients admitted to the Emergency department.

La Tunisie medicale·2020

Search research articles

相关实验视频

Updated: May 30, 2025

Semi-quantitative Assessment Using [18F]FDG Tracer in Patients with Severe Brain Injury

Semi-quantitative Assessment Using [18F]FDG Tracer in Patients with Severe Brain Injury

Published on: November 9, 2018

创伤性脑损伤的AI驱动放射学报告生成

Riadh Bouslimi¹, Houda Trabelsi², Wahiba Ben Abdessalem Karaa²

¹Higher School of Digital Economics, Manouba University, Manouba, Tunisia. riadh.bouslimi@esen.tn.

Journal of imaging informatics in medicine

|January 30, 2025

概括

这项研究介绍了一种人工智能模型,用于生成创伤性脑损伤的放射学报告. 这种新的方法提高了诊断的准确性,并帮助放射科医生和应急医学的学员.

关键词:

在AC-BiFPN中使用.内出血检测检测内出血检测放射学报告的生成变压器架构变压器架构创伤性脑损伤是一种创伤性脑损伤.

更多相关视频

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

Advanced Diffusion Imaging in The Hippocampus of Rats with Mild Traumatic Brain Injury

Advanced Diffusion Imaging in The Hippocampus of Rats with Mild Traumatic Brain Injury

Published on: August 14, 2019

相关实验视频

Last Updated: May 30, 2025

Semi-quantitative Assessment Using [18F]FDG Tracer in Patients with Severe Brain Injury

Semi-quantitative Assessment Using [18F]FDG Tracer in Patients with Severe Brain Injury

Published on: November 9, 2018

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

Advanced Diffusion Imaging in The Hippocampus of Rats with Mild Traumatic Brain Injury

Advanced Diffusion Imaging in The Hippocampus of Rats with Mild Traumatic Brain Injury

Published on: August 14, 2019

科学领域:

医学成像和人工智能医学成像和人工智能
放射学和急诊医学放射学和急诊医学

背景情况:

创伤性脑损伤 (TBI) 在紧急医疗中构成诊断挑战.
及时解释CT和MRI等医疗图像对于患者的结果至关重要.

研究的目的:

开发一种基于人工智能的新方法,用于在头脑创伤病例中自动生成放射学报告.
提高诊断准确度,并支持TBI的临床决策.

主要方法:

集成AC-BiFPN用于多尺度特征提取和异常检测 (例如,内出血).
利用变压器架构,通过建模远程依赖来生成连贯的,与上下文相关的报告.
对RSNA内出血检测数据集的评估.

主要成果:

拟议的AI模型在诊断准确性方面优于传统的基于CNN的模型.
该模型在自动放射学报告生成方面表现出卓越的性能.
人工智能解决方案增强了放射科医生的诊断支持,并作为学员的教育工具.

结论:

将高级特征提取 (AC-BiFPN) 与基于变压器的文本生成相结合,为TBI诊断提供了显著的潜力.
人工智能方法可以改善高压紧急医疗环境中的临床决策.
这项技术可以增强在培训中的医生的学习体验.