title: Combining registration and minimum surfaces for the segmentation of the left ventricle in cardiac cine MR images.
abstract: This paper describes a system to automatically segment the left ventricle in all slices and all phases of cardiac cine magnetic resonance datasets. After localizing the left ventricle blood pool using motion, thresholding and clustering, slices are segmented sequentially. For each slice, deformable registration is used to align all the phases, candidates contours are recovered in the average image using shortest paths, and a minimal surface is built to generate the final contours. The advantage of our method is that the resulting contours follow the edges in each phase and are consistent over time. We demonstrate using 19 patient examples that the results are very good. The RMS distance between ground truth and our segmentation is only 1.6 pixels (2.7 mm) and the Dice coefficient is 0.89.
authors.affiliation: Siemens Corporate Research, Imaging and Visualization Department Princeton, NJ, USA. marie-pierre.jolly@siemens.com
authors.forename: Marie-Pierre
authors.initials: MP
authors.lastname: Jolly
authors.forename: Hui
authors.initials: H
authors.lastname: Xue
authors.forename: Leo
authors.initials: L
authors.lastname: Grady
authors.forename: Jens
authors.initials: J
authors.lastname: Guehring
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D006352:Heart Ventricles / Q000473:pathology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D019028:Magnetic Resonance Imaging, Cine / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D018487:Ventricular Dysfunction, Left / Q000175:diagnosis*