Abstract #2830

Age prediction from time-of-flight MR angiography using deep learning: Comparison of the predicted age among normal, MCI and AD.

Hunjin Chung¹, Yoonho Nam², KoungMi Kang³, Chul-Ho Sohn³, KangHyun Ryu¹, Jinhee Jang², and Dong-Hyun Kim¹

¹Yonsei University, Seoul, Korea, Republic of, ²Seoul St. Mary’s Hospital, Seoul, Korea, Republic of, ³Seoul National University Hospital, Seoul, Korea, Republic of

Time-of-Flight (TOF) MR angiography (MRA) provides meaningful vascular information related to aging. Recently, we have developed a deep learning based chronological age prediction model from 3D TOF data and demonstrated its accuracy in predicting the age of normal volunteers. In this study, to investigate its clinical utilities, we applied the deep learning model to subjects with mild cognitive impairment and Alzheimer’s disease.

This abstract and the presentation materials are available to members only; a login is required.

Join Here