Meeting Banner
Abstract #1990

Reliability of Deep Learning-based MR Image Reconstruction for Cortical Segmentation, Thickness and Intracortical Myelin Mapping

Sang-Young Kim1, Eunju Kim1, Jinwoo Hwang1, Nitish Katoch1, and Chae Jung Park2
1Health Systems, Philips Healthcare, Seoul, Korea, Republic of, 2Department of Radiology, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, Korea, Republic of

Synopsis

Keywords: AI/ML Image Reconstruction, Validation

Motivation: SmartSpeed AI, deep learning-based MR image reconstruction method can be used for scan acceleration, but its clinical applicability for studying brain volumetry and/or cortical myelin has not been investigated.

Goal(s): This study was aimed to quantitatively evaluate the reliability for estimates of cortical thickness and myelin estimated from SmartSpeed AI reconstruction.

Approach: Segmentation performance was evaluated using Dice coefficient and Hausdorff distance and the reliability of estimation for cortical thickness and myelin was assessed using intraclass correlation coefficient.

Results: Comparable segmentation accuracy and reliable estimates of cortical thickness and myelin were obtained from relatively high acceleration factor with SmartSpeed AI reconstruction.

Impact: SmartSpeed AI reconstruction enabled accurate cortical segmentation, and the reliable estimation of cortical thickness and intracortical myelin, suggesting the validity of its clinical applicability with reduced scan time.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.

Keywords