在MRI中使用卷积神经网络和VGG16进行脑瘤细分和检测
Shunmugavel Ganesh1, Ramalingam Gomathi2, Suriyan Kannadhasan3
1Department of Computer Science and Engineering, Study, World College of Engineering, Coimbatore, Tamilnadu, India.
Cancer biomarkers : section A of Disease markers
|April 4, 2025
概括
这项研究引入了一种使用卷积神经网络 (CNN) 的自动化系统,用于在MRI图像中准确检测脑瘤. 该系统利用深度学习来提高诊断速度和精度,改善患者的治疗结果.
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:
- 自动化癌症检测系统对于提高诊断准确性和效率至关重要.
- 卷积神经网络 (CNN) 在分析医疗图像 (如MRI) 进行瘤识别方面显示出显著的前景.
研究的目的:
- 开发和评估使用MRI图像上的CNN用于脑瘤检测和分类的自动化系统.
- 提高癌症诊断的准确性和速度,从而改善患者的治疗结果.
主要方法:
- 利用深度学习和图像处理技术,包括图像增强,细分,数据增强,特征提取和分类.
- 开发了一种基于CNN的模型,用于在MRI扫描中准确检测和分类瘤.
- 采用混合方法,将传统的图像处理与深度学习相结合,以进行可靠的分析.
主要成果:
- 从MRI图像中检测和分类脑瘤的高精度.
- 证明了CNN在学习医疗图像分析复杂特征方面的有效性.
- 该系统实现了98.5%的训练精度,具有高的验证精度和低的验证损失.
结论:
- 深度学习技术,特别是CNN,为自动化用MRI图像检测脑瘤提供了强大的工具.
- 开发的系统可以帮助医疗保健专业人员更快,更准确地诊断癌症,从而改善患者护理.
- 这种方法有可能彻底改变医学图像分析和临床工作流程.
相关概念视频
01:24Magnetic Resonance Imaging
7.6K
Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
7.6K
01:27Imaging Studies IV: Magnetic Resonance Imaging
427
Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...
427