Progress on brain tumor diagnosis and treatment based on deep learning magnetic resonance imaging
YANG Langhuan
FAN Guangtao
LI Zhengfei
XU Yang
ZHENG Jikun
Abstract：The application of artificial intelligence(AI)in the medical field,particularly in the personalized strategies for brain tumor diagnosis and treatment,holds significant potential.However,successfully integrating AI into clinical practice faces numerous challenges.Deep learning(DL)technology efficiently extracts relevant information from extensive medical histories and imaging records,significantly reducing diagnostic time.The application of DL in automated tumor segmentation,classification,and diagnosis enhances the ability to identify tumor phenotypes and brain metastases,thereby supporting real-time decision-making and optimizing preoperative planning.By employing DenseNet and 3D convolutional neural network architectures,DL effectively integrates 2D and 3D MRI data,enhancing the precision of radiological diagnosis and enabling more detailed tumor characterization.This article reviews the research progress of DL magnetic resonance imaging in the diagnosis and treatment of brain tumors.
Keywords：Brain tumorMagnetic resonance imagingDeep learningArtificial intelligence
Publication Date：2025-01-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 91-95 )