[Brain MRI-Based Artificial Intelligence Software in Patients with Neurodegenerative Diseases: Current Status].
So Yeong JeongChong Hyun SuhHo Young ParkHwon HeoWoo Hyun ShimSang Joon KimPublished in: Taehan Yongsang Uihakhoe chi (2022)
The incidence of neurodegenerative diseases in the older population has increased in recent years. A considerable number of studies have been performed to characterize these diseases. Imaging analysis is an important biomarker for the diagnosis of neurodegenerative disease. Objective and reliable assessment and precise detection are important for the early diagnosis of neurodegenerative diseases. Artificial intelligence (AI) using brain MRI applied to the study of neurodegenerative diseases could promote early diagnosis and optimal decisions for treatment plans. MRI-based AI software have been developed and studied worldwide. Representatively, there are MRI-based volumetry and segmentation software. In this review, we present the development process of brain volumetry analysis software in neurodegenerative diseases, currently used and developed AI software for neurodegenerative disease in the Republic of Korea, probable uses of AI in the future, and AI software limitations.
Keyphrases
- artificial intelligence
- deep learning
- machine learning
- big data
- contrast enhanced
- magnetic resonance imaging
- data analysis
- current status
- diffusion weighted imaging
- resting state
- white matter
- magnetic resonance
- physical activity
- convolutional neural network
- cerebral ischemia
- functional connectivity
- risk factors
- smoking cessation
- combination therapy
- health insurance
- case control
- subarachnoid hemorrhage