Enhanced Depth Imaging (EDI) optical coherence tomography (OCT) provides high-definition cross-sectional images of the choroid in vivo, and hence is used in many clinical studies. However, measurement of choroidal thickness depends on the manual labeling, which is tedious and subjective of inter-observer differences. In this paper, we propose a fast and accurate algorithm that could measure the choroidal thickness automatically. The lower boundary of the choroid is detected by searching the biggest gradient value above the retinal pigment epithelium (RPE) and the upper boundary is formed by finding the shortest path of the graph formed by valley pixels using dynamic programming. The average of Dice's Coefficient on 10 EDI-OCT images is 94.3%, which shows good consistency of the algorithm with the manual labeling. The processing time for each image is about 2 seconds.