This paper proposes a new automatic method for liver vessel segmentation by exploiting intensity and shape constraints of 3D vessels. The core of the proposed method is to apply two different strategies: 3D region growing facilitated by bi-Gaussian filter for thin vessel segmentation, and hybrid active contour model combined with K-means clustering for thick vessel segmentation. They are then integrated to generate final segmentation results. The proposed method is validated on abdominal computed tomography angiography (CTA) images, and obtains an average accuracy, sensitivity, specificity, Dice, Jaccard, and RMSD of 98.2%, 68.3%, 99.2%, 73.0%, 66.1%, and 2.56 mm, respectively. Experimental results show that our method is capable of segmenting complex liver vessels with more continuous and complete thin vessel details, and outperforms several existing 3D vessel segmentation algorithms.

Autonomous exploration in unknown environm-ents is a fundamental task of Unmanned Aerial Vehicles (UAVs). To choose exploration goals wisely, we propose an information-driven exploration strategy by applying the fast marching method to exploration of UAVs. A frontier point detection algorithm is designed to obtain Candidate Goals (CGs) by utilizing the structural characteristics of the octree-based map. With the sum of the information gain during the exploration journey as an evaluation indicator, we present a novel utility function to evaluate CGs by considering the trade-off between information gain and travel consumption. Given the effect of the environment on UAVs, UAVs are required to march aggressively in the Euclidean Symbol Distance Field (ESDF) to calculate the flight time, which is defined as the travel consumption. The uncertainty of the environment is minimized gradually by maximizing the utility function during each exploration journey. To take full advantage of the mobility of UAVs, we perform B-spline trajectory optimization and yaw angle planning based on the fast marching paths. We conduct sufficient comparison and evaluation experiments in simulation environments. Experimental results show the superiority of the proposed exploration strategy. The code related to the experiments will be published at https://github.com/BoLeiChen /fastmarching-exploration.