Meeting Banner
Abstract #4995

Shading Artifact Suppression using Relaxation Map and Machine Learning-based Region Detection for Quantitative Susceptibility Mapping

Taichiro Shiodera1, Takashi Watanabe1, Tomoyuki Takeguchi1, Naotaka Sakashita2, Masao Yui2, and Samir D. Sharma3

1Toshiba Corporation, Kawasaki, Japan, 2Toshiba Medical Systems Corporation, Otawara, Japan, 3Toshiba Medical Research Institute, Mayfield Village, OH, United States

We propose a dipole inversion method for improving quantitative susceptibility mapping. In conventional methods, shading artifacts often occur near the longitudinal fissure (LF) region of the estimated susceptibility map. Here, we propose an algorithm for LF region detection and regularized inversion, to reduce the shading artifacts. The LF region is automatically detected using information from the T2* map as well as training datasets via machine learning. The proposed method eliminates shading artifacts near the LF region in the susceptibility maps, while also showing negligible change in regions that do not suffer from shading artifacts, such as the basal ganglia.

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