Abstract
This paper presents a new method for automated SmartPrep tracker positioning in liver MRI scans. SmartPrep is used to monitor the contrast bolus signal in order to detect the arrival time of the bolus. Accurately placing the tracker in the aorta while viewing three planar scout images is a difficult task for the operator and is an important problem from the workflow standpoint. The development of an automated SmartPrep tracker would therefore help to improve workflow in liver MRI scans. In our proposed method, the aorta is detected using AdaBoost (which is a machine learning technique) by searching around the CSF in the spinal cord. Analysis of scout scan images showed that our detection method functioned properly for a variety of axial MR images without intensity correction. A total of 234 images reconstructed from the datasets of 64 volunteers were analyzed, and the results showed that the detection error for the aorta was approximately 3 mm.
