Our finding corroborates that schizophrenia is associated with widespread alterations in subcortical brain structure and the subcortical structural information provides prominent features in diagnostic classification.
Here we propose a potential solution by first learning a structural-to-functional transformation in brain MRI, and further synthesizing spatially matched functional images from large-scale structural scans.
no code implementations • 15 Jan 2020 • Haoran Sun, Xueqing Liu, Xinyang Feng, Chen Liu, Nanyan Zhu, Sabrina J. Gjerswold-Selleck, Hong-Jian Wei, Pavan S. Upadhyayula, Angeliki Mela, Cheng-Chia Wu, Peter D. Canoll, Andrew F. Laine, J. Thomas Vaughan, Scott A. Small, Jia Guo
Together, these studies validate our hypothesis that a deep learning approach can potentially replace the need for GBCAs in brain MRI.
Numerous studies have established that estimated brain age, as derived from statistical models trained on healthy populations, constitutes a valuable biomarker that is predictive of cognitive decline and various neurological diseases.