Medical imaging scanners now exist that can generate 4D cardiac images. Since the heart moves, cardiac anatomy and physiology can be studied using 4D image sequences. Interactive manual 4D image analysis can be time-consuming and error-prone - automatic and semi-automatic methods have many advantages over manual segmentation. This paper describes a procedure for performing semi-automatic image segmentation on 4D image sequences. Our procedure is based on a small set of user-defined image-segmentation cues specified at certain time points in the sequence. These cues are then automatically interpolated or extrapolated for the remaining time points. The complete set of cues is interpreted and used to generate a sequence of image processing operations (such as operators for image enhancement, morphological processing, and region segmentation) that can subsequently segment the 4D image. This procedure permits 4D cardiac image segmentation with only a small amount of user interaction. The proposed approach compares favorably to results generated by defining cues on each individual volume and to results generated completely manually. The 4D approach also requires significantly less interaction time than pure manual analysis.
All Science Journal Classification (ASJC) codes
- Signal Processing
- Computer Vision and Pattern Recognition