Keywords: MR-Guided Radiotherapy, Radiotherapy, Deep Learning, MR-only, Radiation Therapy Planning
Motivation: Deep Learning (DL) is an enabling technology for MR-only Radiation Therapy Planning in terms of 1) MR to synthetic CT conversion and 2) automated Organ-At-Risk (OAR) segmentation.
Goal(s): To investigate the feasibility of DL based MR-only RT planning using accelerated MR protocols with <5mins scan time (not including tumor depiction).
Approach: Quantitative evaluation of synthetic CTs in terms of mean absolute error (MAE) and OAR segmentations in terms of Likert Score analysis.
Results: Preliminary results demonstrate the feasibility of DL-based MR-only RT in <5min scan time with only minor degradation of synthetic CT and OAR segmentation quality.
Impact: Deep Learning is an enabling technology for MR-only Radiation Therapy Planning. Here we demonstrate its capabilities for 1) synthetic CT conversion and 2) Organ-At-Risk (OAR) segmentation in <5min MR 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.
Keywords