We present an automated approach for the segmentation of airways in CT datasets. The approach utilizes the Gradient Vector Flow and consists of two main processing steps. Initially, airway-like structures are identified and their centerlines are extracted. These centerlines are used in a second step to initialize the actual segmentation of the corresponding airways. An evaluation on 20 clinical...

The paper aims at segmenting an image. The goal of image segmentation is to simplify and/or change the representation of an image into something that is more meaningful and simpler to analyze. In this paper we consider segmenting the image using the shortest spanning tree. To find the shortest spanning tree the image is first mapped into a graph. There have already been research conducted in th...

Lidayová, K. 2017. Fast Methods for Vascular Segmentation Based on Approximate Skeleton Detection. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology 1496. 79 pp. Uppsala: Acta Universitatis Upsaliensis. ISBN 978-91-554-9874-0. Modern medical imaging techniques have revolutionized health care over the last decades, providing clinicians with high-...

The segmentation of tree-like tubular structures such as coronary arteries and airways is an essential step for many 3D medical imaging applications. Statistical tracking techniques for the extraction of elongated structures have received considerable attention in recent years due to their robustness against image noise and pathological changes. However, most tracking methods are limited to a s...

This is a critical review of the paper “An Airway Tree-shape Model for Geodesic Airway Branch Labeling” written by Feragen et. al. [1]. This paper presents a method for airway branch labeling by computing geodesic deformations between mathematical airway tree-shape models. The authors claim that the labeling results are good taking the large variation in the training set into account. Even thou...

We present a new algorithm for automatic and interactive segmentation of neuron structures from electron microscopy (EM) images. Our method selects a collection of nodes from the watershed mergng tree as the proposed segmentation. This is achieved by building a onditional random field (CRF) whose underlying graph is the merging tree. The maximum a posteriori (MAP) prediction of the CRF is the o...

This study is a contribution to assess the high resolution digital aerial imagery for semi-automatic analysis of tree species identification. To maximize the benefit of such data, the object-based classification was conducted in a mixed forest plantation. Two subsets of an UltraCam D image were geometrically corrected using aero-triangulation method. Some appropriate transformations were perfor...

This paper introduces a direction-sensitive and locally reorientable compact binary tree, called the Z tree, for representing digital images. A rotation operation is de ned on a subset of its node, called square nodes, to spatially reorganize the four grand children of any given square-node. The goal is to adapt the Z tree in order to produce a minimal cutset representation of homogeneous regio...