qMT has been suggested as a biomarker in Glioblastoma patients. However, reconstruction involves a computationally expensive fitting procedure involving the Bloch-McConnell equations. In this work, the use of neural networks was investigated to perform the fit and to compute uncertainty heatmaps to identify regions of potential error. The dataset consisted of 164 scans from N=41 glioblastoma patients (33=training, 8=testing). Models were evaluated using MAE and correlation in the whole-head volumes and specific ROIs. The model output agreed with a conventional curve-fitting algorithm (r=0.93, and <1% error) with speed up factors of 240000x. Uncertainty predictions were correlated with prediction error (r=0.59).
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.
Keywords