Keywords: Machine Learning/Artificial Intelligence, Data AnalysisEstimating patient height and weight is used to determine the optimum SAR (Signal Modelling) for the patient. We used a deep learning approach to first generate the point cloud of the person (Data Processing) followed by prediction of the height and weight (Data Analysis). This tackles the problems of heavy occlusion which occurs in the MR imaging scenario in the form of coils/blankets and different positions in which the patient will be placed. We achieved a MAE score of 4.9 cm on the height and 6.2 kg on the weight. This is a promising solution to an important problem.
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