基于GPU的并行处理技术,用于增强大脑磁共振成像分析:对最近进展的回顾
Ayca Kirimtat1, Ondrej Krejcar1
1Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Kralove, Rokitanskeho 62, 500 03 Hradec Kralove, Czech Republic.
Sensors (Basel, Switzerland)
|March 13, 2024
概括
基于图形处理单元 (GPU) 的并行处理加速了医疗成像分析. 这篇评论强调了它在脑MRI任务中的使用,显示了减少计算时间和未来的挑战.
科学领域:
- 医疗成像医学成像
- 计算科学 计算科学
- 神经科学是一个神经科学.
背景情况:
- 医学成像,特别是磁共振成像 (MRI),对于诊断大脑疾病至关重要.
- 在MRI中复杂的图像分析任务需要大量的计算资源.
- 基于图形处理单元 (GPU) 的并行处理为加快这些计算提供了解决方案.
研究的目的:
- 提供关于基于GPU的并行处理在脑MRI分析中的应用的综合文献综述.
- 强调GPU加速在提高各种医学成像技术效率方面的作用.
- 确定GPU加速脑MRI分析的进展和剩余挑战.
主要方法:
- 对2019年至2023年期间发表的文献进行系统审查.
- 对专注于基于GPU的脑MRI任务并行处理的文章进行分析.
- 根据任务,技术,MRI序列和处理结果对研究进行分类.
主要成果:
- 基于GPU的并行处理显著降低了脑MRI分析的计算运行时间.
- 在图像分类,物体检测,细分,注册和检索方面取得了明显的进步.
- 确定了加速医学成像计算进步的关键领域.
结论:
- 基于GPU的并行处理对于医疗成像中的时间效率计算至关重要,特别是对大脑MRI.
- 审查的方法在减少实时医疗反计算时间方面取得了实质性进展.
- 需要进一步的研究来解决现有的障碍,并优化未来医疗分析中的GPU利用.
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