What is it about?
Recent improvements in the field of Machine Learning (ML) and Artificial Intelligence (AI) have allowed a pioneering era in brain imaging; where complex neuroimaging data can now be understood. The pivotal role of AI and ML algorithms in the interpretation, analysis and clinical application of brain imaging modalities is extensively presented in this review article. The field of brain imaging has seen remarkable progress in image segmentation and registration thanks to advancements in AI and deep learning.
Featured Image
Photo by jesse orrico on Unsplash
Why is it important?
These technologies have proven essential in categorizing brain images, as well as identifying neurological conditions such as Alzheimer’s disease. In the realm of functional brain imaging, AI and deep learning techniques decode intricate activity patterns, offering insights into cognitive processes and disorders like neurodegenerative diseases. The implications of these developments are far-reaching, ranging from enhancing our understanding of neurological disorders to pioneering innovative treatment methods. With the aid of AI, predictive models based on brain imaging data have become crucial in forecasting and customizing treatments for neurodegenerative diseases. This integration of diverse data sources facilitates personalized patient care.
Perspectives
This review highlights the possibilities of combining AI and ML with neuroimaging to develop personalized predictive models for highly targeted and effective therapy. In the field of neuroinformatic, these technologies allow for the examination of vast amounts of data, uncovering new biomarkers and patterns of functional brain activity. Furthermore, the advancement of brain-computer interfaces based on neuroimaging shows potential in areas such as neuro-rehabilitation and human-computer interaction. Nevertheless, there are still challenges to be addressed, including the diversity of data, the interpretability of deep learning models, and ethical considerations. In summary, this comprehensive overview discusses the transformative effects of AI and ML in brain imaging and explores future directions in this field.
Ravi Kant Singh
Amity University
Read the Original
This page is a summary of: Transforming brain research: Neuroimaging breakthroughs driven by AI, January 2025, American Institute of Physics,
DOI: 10.1063/5.0248504.
You can read the full text:
Contributors
The following have contributed to this page
