Real-time segmentation by Active Geometric Functions

Recent advances in 4D imaging and real-time imaging provide image data with clinically important cardiac dynamic information at high spatial or temporal resolution. However, the enormous amount of information contained in these data has also raised a challenge for traditional image analysis algorithms in terms of efficiency. In this paper, a novel deformable model framework, Active Geometric Functions (AGF), was introduced to tackle the real time segmentation problem. As an implicit framework paralleling to level set, AGF has mathematical advantages in efficiency and computational complexity as well as several flexible feature similar to level set framework. AGF was demonstrated in two cardiac applications: endocardial segmentation in 4D ultrasound and myocardial segmentation in MRI with super high temporal resolution. In both applications, AGF can perform real-time segmentation in several milliseconds per frame, which was less than the acquisition time per frame. Segmentation results ...

• Type: Journal
• Year: 2010
• Where: CMPB
• Authors: Qi Duan, Elsa D. Angelini, Andrew F. Laine
• Keywords: CMPB 2010, Real-time Segmentation, Temporal Resolution, Time Segmentation Problem