医学
人工智能
分割
标准化
神经影像学
医学物理学
深度学习
磁共振成像
鉴定(生物学)
放射科
病理
机器学习
计算机科学
植物
精神科
生物
操作系统
作者
Ezekiel Chukwujindu,Hafsa Faiz,Sara AI-Douri,Khunsa Faiz,A. Sequeira
标识
DOI:10.1016/j.ejrad.2024.111509
摘要
Artificial intelligence (AI) is a rapidly evolving field with many neuro-oncology applications. In this review, we discuss how AI can assist in brain tumour imaging, focusing on machine learning (ML) and deep learning (DL) techniques. We describe how AI can help in lesion detection, differential diagnosis, anatomic segmentation, molecular marker identification, prognostication, and pseudo-progression evaluation. We also cover AI applications in non-glioma brain tumours, such as brain metastasis, posterior fossa, and pituitary tumours. We highlight the challenges and limitations of AI implementation in radiology, such as data quality, standardization, and integration. Based on the findings in the aforementioned areas, we conclude that AI can potentially improve the diagnosis and treatment of brain tumours and provide a path towards personalized medicine and better patient outcomes.
科研通智能强力驱动
Strongly Powered by AbleSci AI