Automatic brain MRI motion artifact detection based on end-to-end deep learning is similarly effective as traditional machine learning trained on image quality metrics

Pál Vakli,Béla Weiss,János Szalma,Péter Barsi, István Gyuricza,Péter Kemenczky,Eszter Somogyi,Ádám Nárai,Viktor Gál,Petra Hermann,Zoltán Vidnyánszky

Medical Image Analysis（2023）

引用 0|浏览2

暂无评分

摘要

•N = 2072 brain MRI scans rated by neuroradiologists from a clinical perspective.•Lightweight 3D CNN achieves ∼94% balanced accuracy in identifying severe head motion.•SVM trained on IQMs achieves comparably high balanced accuracy of ∼88%.•No significant difference between models regarding confusion matrix, error rate, ROC.

查看译文

关键词

mri,deep learning,end-to-end

AI 理解论文

溯源树

样例

生成溯源树，研究论文发展脉络

Chat Paper

正在生成论文摘要