title: Auto-alignment of knee MR scout scans through redundant, adaptive and hierarchical anatomy detection.
abstract: 3D knee magnetic resonance (MR) scout scan is an emerging imaging sequence that facilitates technicians in aligning the imaging planes of diagnostic high resolution MR scans. In this paper, we propose a method to automate this process with the goal of improving the accuracy, robustness and speed of the workflow. To tackle the various challenges coming from MR knee scout scans, our auto-alignment method is built upon a redundant, adaptive and hierarchical anatomy detection system. More specifically, we learn 1) a hierarchical redudant set of anatomy detectors, and 2) ensemble of group-wise spatial configurations across different anatomies, from training data. These learned statistics are integrated into a comprehensive objective function optimized using an expectation-maximization (EM) framework. The optimization provides a new framework for hierarchical detection and adaptive selection of anatomy primitives to derive optimal alignment. Being extensively validated on 744 clinical datasets, our method achieves high accuracy (sub-voxel alignment error), robustness (to severe diseases or imaging artifacts) and fast speed ( 5 sees for 10 alignments).
authors.affiliation: Siemens Medical Solutions, USA.
authors.forename: Yiqiang
authors.initials: Y
authors.lastname: Zhan
authors.forename: Maneesh
authors.initials: M
authors.lastname: Dewan
authors.forename: Xiang Sean
authors.initials: XS
authors.lastname: Zhou
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007717:Knee / Q000033:anatomy & histology*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008953:Models, Anatomic; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique