Multi-Object Detection and Segmentation of Brain Structures Based on Dynamic Programming
Jue Wu, Albert C. S. Chung · Medical Image Computing and Computer-Assisted Intervention · 2009
This work aims to design a detection and segmentation method using a graphical model in the context of multi-object brain image seg- mentation. We resort to dynamic programming as the optimization strat- egy to find the global minimum energy for the relation graph. Compared to other graphical models like tree structures, the proposed approach offers flexibility in accommodating more interactions among objects and thus can inhibit error propagation. Also, the new method is able to de- tect and segment a larger number of objects by searching for the global optimum energy in an efficient way. Experimental results show that the proposed approach achieves a comparable accuracy to other state-of-the- art methods.