Background Blood vessel segmentation is a topic of high interest in medical image analysis
since the analysis of vessels is crucial for diagnosis, treatment planning and execution, and …

Motivation Large-scale neuronal morphologies are essential to neuronal ty**, connectivity
characterization and brain modeling. It is widely accepted that automation is critical to the …

Creating road maps is essential to the success of many applications such as autonomous
driving and city planning. Most approaches in industry focus on leveraging expensive …

In recent years, contextual models that exploit maps have been shown to be very effective
for many recognition and localization tasks. In this paper we propose to exploit aerial images …

Top-k error is currently a popular performance measure on large scale image classification
benchmarks such as ImageNet and Places. Despite its wide acceptance, our understanding …

Finding the centerline and estimating the radius of linear structures is a critical first step in
many applications, ranging from road delineation in 2D aerial images to modeling blood …

We propose a robust and accurate method to extract the centerlines and scale of tubular
structures in 2D images and 3D volumes. Existing techniques rely either on filters designed …

Vector drawing is a popular representation in graphic design because of the precision,
compactness and editability offered by parametric curves. However, prior work on line …

This paper provides a hierarchical method for urban road extraction. It consists of (1)
obtaining the road region of interest from a VHR image,(2) hierarchically representing this …

Automated road network extraction from remote sensing imagery remains a significant
challenge despite its importance in a broad array of applications. To this end, we explore …