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Updated: Sep 15, 2025

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
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精确的实时脑瘤检测和分类使用优化的YOLOv5架构

M Saranya1, R Praveena2

  • 1Department of Biomedical Engineering, Mahendra Institute of Technology, Namakkal, India. saranyabm1990@gmail.com.

Scientific reports
|July 12, 2025
PubMed
概括

这项研究引入了一个结合全卷积神经网络 (FCNN) 和你只看一次版本5 (YOLOv5) 的深度学习模型,用于准确地识别和分类脑瘤,并从MRI扫描中进行分类. 拟议的方法实现了98.80%的平均准确性,提高了医学成像诊断的性能.

关键词:
脑瘤的分类 脑瘤的分类大脑瘤检测检测大脑瘤的检测.一个完全卷积的神经网络.磁共振成像细分 磁共振成像细分瘤局部化的局部化在 YOLOv5 架构中,YOLOv5 架构是

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