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深度学习技术在乳房MRI中的演变和临床影响

Tomoyuki Fujioka¹, Shohei Fujita², Daiju Ueda³

¹Department of Diagnostic Radiology, Tokyo Medical and Dental University, Tokyo, Japan.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine

|October 30, 2024

概括

深度学习 (DL) 显著提高了乳房MRI诊断,改善了图像质量和病变分类. 这项技术为乳腺癌提供了个性化的治疗策略,尽管临床整合需要进一步的研究和道德准则.

科学领域:

医疗成像医学成像
人工智能的人工智能
在瘤学瘤学.

背景情况:

深度学习 (DL) 正在改变医学成像分析.
乳腺MRI应用正在迅速发展,随着人工智能集成.
准确的乳腺癌诊断和结果预测至关重要.

研究的目的:

审查DL对乳腺MRI的影响.
探索DL在图像重建,分类,细分和预测中的应用.
讨论DL在临床乳腺癌护理中的潜力和挑战.

主要方法:

在乳腺MRI中对深度学习模型 (CNN,RNN,GAN) 的审查.
在各种乳腺MRI任务中分析DL应用.
在乳腺癌诊断和预后中对DL进行当前研究的综合.

主要成果:

DL可以提高乳房MRI图像的质量,准确性和效率.
DL模型增强了良性和恶性病变之间的差异化.
DL准确预测乳腺癌患者的治疗反应和复发风险.

结论:

深度学习正在彻底改变乳腺癌诊断和个性化医学.
DL提供了对疾病行为和治疗疗效的更深入的见解.
乳腺MRI中DL的临床整合需要进一步的验证和伦理考虑.

关键词:

人工智能的人工智能是人工智能.乳房乳房乳房乳房深度学习是一种深度学习.磁共振成像技术的使用神经网络的神经网络的神经网络

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