Distance transformation and skeleton for shape feature analysis
IAPR Proceedings of the international workshop on Visual form: analysis and recognition
Detection of 3-D Simple Points for Topology Preserving Transformations with Application to Thinning
IEEE Transactions on Pattern Analysis and Machine Intelligence
On digital distance transforms in three dimensions
Computer Vision and Image Understanding
Finding the minimal set of maximum disks for binary objects
Graphical Models and Image Processing
Efficient shape representation by minimizing the set of centres of maximal discs/spheres
Pattern Recognition Letters
Distance-ordered homotopic thinning: a skeletonization algorithm for 3D digital images
Computer Vision and Image Understanding
A parallel 3D 12-subiteration thinning algorithm
Graphical Models and Image Processing
3-D Image Processing Algorithms
3-D Image Processing Algorithms
Digital Picture Processing
New sequential exact Euclidean distance transform algorithms based on convex analysis
Image and Vision Computing
Isthmus-based 6-directional parallel thinning algorithms
DGCI'11 Proceedings of the 16th IAPR international conference on Discrete geometry for computer imagery
Euclidean distance transform of digital images in arbitrary dimensions
PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing
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In this article, we present the Euclidean distance transformation (EDT) of three-dimensional (3D) binary pictures and applications, with stress on Dr. Toyofumi Saito's work in collaboration with one of the authors. First, EDT, skeletons, and reverse EDT are defined, and then the algorithms to perform them are presented. Next, a sequential-type 3D thinning algorithm that preserves the topology of an input object is introduced. This algorithm is derived by combining an ordinary two-dimensional thinning algorithm with EDT. Finally, applications to medical image processing are presented such as automated path finding in virtual endoscopy, as well as analysis of 3D pathological sample images. Dr. Toyofumi Saito, an associate professor who was one of the most active researchers in the field of image processing in Japan and a young leader of the author's laboratory, and who was initially scheduled to be the first author of this paper, passed away on 26 October 2000. We have lost a most reliable and most promising colleague, an experienced supervisor, and a very sincere friend. He is deeply missed by all in his family, his friends, and his colleagues. On behalf of the laboratory the authors wish to dedicate this short note in memory of Dr. Toyofumi Saito and to express our sincere condolences to his loved ones.