在MRI中对脑瘤分析进行深度学习的审查
Felix J Dorfner1, Jay B Patel1, Jayashree Kalpathy-Cramer2
1Athinoula A. Martinos Center for Biomedical Imaging, 149 13th St, Charlestown, MA, 02129, USA.
NPJ precision oncology
|January 3, 2025
概括
深度学习 (DL) 增强了MRI中的脑瘤分析,用于诊断和个性化医疗. 这篇评论探讨了DL的研究.
科学领域:
- 人工智能在医学中的应用
- 神经成像分析分析 神经成像分析
- 瘤学研究研究
背景情况:
- 深度学习 (DL) 为临床应用提供先进的计算工具.
- 磁共振成像 (MRI) 在脑瘤诊断和管理中至关重要.
- 客观和可重复的测量对于有效的患者护理至关重要.
研究的目的:
- 审查深度学习 (DL) 在脑瘤护理中的变革潜力.
- 讨论当前在神经成像分析中的DL应用.
- 确定瘤学DL的局限性和未来的机会.
主要方法:
- 关于深度学习在脑瘤MRI中的应用的文献综述.
- 分析DL在细分,量化和分类中的作用.
- 探索DL用于预测瘤特征和患者结果.
主要成果:
- DL促进了MRI中的自动瘤细分,量化和分类.
- DL允许客观和可重现的测量用于诊断和监测.
- 在预测瘤类型,等级,基因突变和生存结果方面,DL显示出前景.
结论:
- 深度学习正在彻底改变脑瘤分析和个性化医学.
- 在神经成像中使用DL可以提高诊断准确性和治疗计划.
- 需要进一步的研究来克服局限性,并充分实现DL在神经瘤学的潜力.
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