Semiautomatic 4D analysis of cardiac image sequences

Medical imaging scanners now exist that can generated 4D cardiac images (time sequences of 3D volumes). Since the heart is an organ that exhibits motion, examining its image characteristics with a 4D image can give useful information about its condition. For multi-dimensional image segmentation, semi-automatic methods have many advantages over manual segmentation. This paper describes a procedure for performing semi-automatic image segmentation and analysis upon a 4D cardiac image. This procedure involves the input of user-defined information (cues) at certain time points of the sequence. These cues are then automatically interpolated or extrapolated for the remaining time points. The analysis system interprets the completed sequence of cues to generate a list of image processing functions that can subsequently segment and analyze the 4D image. This paradigm has been implemented using INTERSEG, an existing 3D cue-based analysis system. This cue-based analysis procedure permits 4D cardiac image segmentation with a small amount of user interaction. Performance of the proposed 4D image analysis system compares favorably to results generated by defining cues on each individual volume, as well as manual techniques. Further, the 4D approach requires significantly less interaction time than a 3D-only approach.