Generating skeletons and centerlines from the distance transform

Niblack, Carlton Wayne; Gibbons, Phillip B.; Capson, David W.

doi:10.1016/1049-9652(92)90026-t

Cited by 106 publications

(43 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…For some applications, an exact EDT is required. For example, various approximations of the EDT have been used to generate skeletons of binary objects [1], [24], but only the exact EDT can produce an accurate skeleton that is reversible (i.e., allows exact reconstruction of the object), rotation invariant, and minimal [13]. The 3D EDT has recently been used to generate skeletons of radiosurgical targets (e.g., brain tumors) for treatment planning and optimization in multiisocentric stereotactic radiosurgery [45], [46].…”

Section: Introductionmentioning

confidence: 99%

A linear time algorithm for computing exact Euclidean distance transforms of binary images in arbitrary dimensions

Maurer

Qi²,

Raghavan

2003

IEEE Trans. Pattern Anal. Machine Intell.

805

523

View full text Add to dashboard Cite

Abstract-A sequential algorithm is presented for computing the exact Euclidean distance transform (DT) of a k-dimensional binary image in time linear in the total number of voxels N. The algorithm, which is based on dimensionality reduction and partial Voronoi diagram construction, can be used for computing the DT for a wide class of distance functions, including the L p and chamfer metrics. At each dimension level, the DT is computed by constructing the intersection of the Voronoi diagram whose sites are the feature voxels with each row of the image. This construction is performed efficiently by using the DT in the next lower dimension. The correctness and linear time complexity are demonstrated analytically and verified experimentally. The algorithm may be of practical value since it is relatively simple and easy to implement and it is relatively fast (not only does it run in OðNÞ time but the time constant is small). A simple modification of the algorithm computes the weighted Euclidean DT, which is useful for images with anisotropic voxel dimensions. A parallel version of the algorithm runs in OðN=pÞ time with p processors.

show abstract

Section: Introductionmentioning

confidence: 99%

A linear time algorithm for computing exact Euclidean distance transforms of binary images in arbitrary dimensions

Maurer

Qi²,

Raghavan

2003

IEEE Trans. Pattern Anal. Machine Intell.

805

523

View full text Add to dashboard Cite

show abstract

“…Our algorithm detects ridges by extracting the strict maxima (i.e. a cell with value stricly greater than any of its nearest neighbours [24]) of the discrete DEM. Next, we use an image processing transformation (the Hough Transform) on a binary image containing the local maxima points which lets us rank the detected lines in the Hough parameter space.…”

Section: Axial Lines As Ridges On Isovist Fieldsmentioning

confidence: 99%

Automatic Extraction of Hierarchical Urban Networks: A Micro-Spatial Approach

Carvalho¹,

Batty

2004

Computational Science - ICCS 2004

View full text Add to dashboard Cite

Abstract. We present an image processing technique for the identification of 'axial lines' [1] from ridges in isovist fields first proposed by Rana [2,3]. These ridges are formed from the maximum diametric lengths of the individual isovists, sometimes called viewsheds, that make up the isovist fields [4]. We discuss current strengths and weaknesses of the method, and show how it can be implemented easily and effectively.

show abstract

“…Based on the contour map, there are several known skeleton extraction methods in the literature [17]: Boundary Peeling (also called thinning) [12], Distance Coding (distance transformation) [13] and Polygon-based Voronoi Methods [2]. Because it is simple and fast, we use the distance transformation method to generate a skeleton.…”

Section: Skeleton Generationmentioning

confidence: 99%

An Optimization Approach for Radiosurgery Treatment Planning

Ferris¹,

Lim²,

Shepard³

2002

SIAM J. Optim.

View full text Add to dashboard Cite

We outline a new approach for radiosurgery treatment planning, based on solving a series of optimization problems. We consider a specific treatment planning problem for a specialized device known as the Gamma Knife, that provides an advanced stereotactic approach to the treatment of tumors, vascular malformations, and pain disorders within the head. The sequence of optimization problems involves nonlinear and mixed integer programs whose solution is required in a given planning time (typically less than 30 minutes). This paper outlines several modeling decisions that result in more efficient and robust solution. Furthermore, it outlines a new approach for determining starting points for the nonlinear programs, based on a skeletonization of the target volume. Treatment plans are generated for real patient data that show the efficiency of the approach.

show abstract

Generating skeletons and centerlines from the distance transform

Cited by 106 publications

References 18 publications

A linear time algorithm for computing exact Euclidean distance transforms of binary images in arbitrary dimensions

A linear time algorithm for computing exact Euclidean distance transforms of binary images in arbitrary dimensions

Automatic Extraction of Hierarchical Urban Networks: A Micro-Spatial Approach

An Optimization Approach for Radiosurgery Treatment Planning

Contact Info

Product

Resources

About