ENIGMA, big data, and the human brain: worldwide neuroimaging & genomics of 30 brain diseases in 100,000 people from 45 countries (Conference Presentation)

Paul M. Thompson

doi:10.1117/12.2664587

3 April 2023 ENIGMA, big data, and the human brain: worldwide neuroimaging & genomics of 30 brain diseases in 100,000 people from 45 countries (Conference Presentation)

Paul M. Thompson

Author Affiliations +

Proceedings Volume 12464, Medical Imaging 2023: Image Processing; 124640G (2023) https://doi.org/10.1117/12.2664587
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Abstract

Since 2009, we have led the ENIGMA Consortium, a worldwide alliance of over 2,000 scientists studying 30 brain diseases in 45 countries. Pooling multimodal brain images and genomic data from over 100,000 people worldwide, ENIGMA's 51 working groups have published the largest neuroimaging studies of schizophrenia, bipolar disorder, depression, PTSD, addiction, and Parkinson’s disease, OCD, ADHD, epilepsy, HIV and autism. ENIGMA’s genomic screens of more than 70,000 people’s brain scans and genome-wide data have brought together experts from 300 institutions to unearth genetic variants that affect brain structure, connectivity, functional brain synchrony, and disease risk. In this talk, we cover current and future challenges in analyzing medical imaging and genomic data worldwide. We describe the vast power of AI and deep learning methods for disease diagnosis, subtyping, and staging, and for discovering environmental, medication, and genomic factors that promote or resist disease. We illustrate the talk with mathematical examples from meta-analysis, AI and federated algorithms for multimodal image harmonization, predictive modeling, and even novel image synthesis and enhancement.

Conference Presentation

Citation Download Citation

Paul M. Thompson "ENIGMA, big data, and the human brain: worldwide neuroimaging & genomics of 30 brain diseases in 100,000 people from 45 countries (Conference Presentation)", Proc. SPIE 12464, Medical Imaging 2023: Image Processing, 124640G (3 April 2023); https://doi.org/10.1117/12.2664587

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