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Distance transform

About: Distance transform is a research topic. Over the lifetime, 2886 publications have been published within this topic receiving 59481 citations.


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Book ChapterDOI
11 Oct 2000
TL;DR: An automatic centerline determination algorithm for three dimensional virtual bronchoscopy CT image is presented and its performance is encouraging.
Abstract: Centerline extraction is the basis to understand three dimensional structure of the lung. In this paper, an automatic centerline determination algorithm for three dimensional virtual bronchoscopy CT image is presented. This algorithm has two main components. They are end points retrieval algorithm and graph based centerline algorithm. The end points retrieval algorithm first constructs a binary tree which links up all necessary center points of each region in each slice from segmented lung airway tree volume data. Next, it extracts the end points of the lung airway tips from the binary tree. The graph based centerline algorithm reads the end points and applies distance transform to yield a distance map which shows all shortest paths from the start point to those end points. Then, modified Dijkstra shortest path algorithm is applied in the centerline algorithm to yield the centerline of the bronchus. Our algorithm is tested with various CT image data and its performance is encouraging.

19 citations

Journal ArticleDOI
TL;DR: The segmentation problem originally formulated for crossing fibres observed in a two‐dimensional image can be reformulated as a segmentsation problem in a three‐dimensional images through two new image transforms.
Abstract: Summary Segmentation of crossing fibres is a complex problem of image processing. In the present paper, various solutions are presented basing on tools of morphological image processing. Two new image transforms are introduced – the lineal distance transform and the chord length transform. Both transforms are applied to two-dimensional images and their results are three-dimensional images. Thus, the segmentation problem originally formulated for crossing fibres observed in a two-dimensional image can be reformulated as a segmentation problem in a three-dimensional image. This can be solved by a segmentation in the three-dimensional image. Algorithms for the lineal distance transform and the chord length transform are given and their use in image analysis is demonstrated. Furthermore, the chord length distribution function of the foreground of a binary image can efficiently be estimated via the chord length transform.

19 citations

Proceedings ArticleDOI
TL;DR: A quantitative measure of image enhancement that is related to the Weber's law of the human visual system is considered and the best parameters for image enhancement can be found for each image-signal to be processed separately.
Abstract: In this paper, a new method of image enhancement is introduced. The method is based on the tensor (or vectorial) representation of the two-dimensional image with respect to the Fourier transform. In this representation, the image is defined as a set of one-dimensional (1-D) image-signals that split the Fourier transform into a set of 1-D transforms. As a result, the problem of the image enhancement is reduced to the 1-D processing the splitting signals. The splitting of the image yields a simple model for the image enhancement, when by using only a few image-signals it is possible to achieve the image enhancement that is comparative to the known class of the frequency domain based parametric image enhancement algorithms, that are used widely for the object detection and visualization. A quantitative measure of image enhancement that is related to the Weber's law of the human visual system is considered. Based on the quantitative measure the best parameters for image enhancement can be found for each image-signal to be processed separately. Examples of image-signals and their contributions in process of enhancement of an image 256×256 are given.

19 citations

Journal ArticleDOI
Dong-Jin Yoo1
TL;DR: Wang et al. as discussed by the authors proposed a new projection image generation algorithm that automatically and robustly generates 2D projection image data using the volumetric distance field and triply periodic minimal surface (TPMS) pore morphology.
Abstract: Advanced additive manufacture (AM) techniques have been developed to generate three-dimensional (3D) tissue scaffolds with complex topography and controlled internal pore architecture. Among the various AM methods, projection stereolithography (PSL) can be used to fabricate intricate 3D tissue scaffolds that can be engineered to mimic the microarchitecture of tissues. PSL system offers the advantages of enhanced fabrication speed and accuracy compared with conventional stereolithography system. To design and fabricate a complex 3D scaffold, we propose a new projection image generation algorithm that automatically and robustly generates 2D projection image data. The method uses the volumetric distance field (VDF) and triply periodic minimal surface (TPMS) pore morphology. By the creative combination of VDF and TPMS-based pore architecture, we can easily and rapidly generate projection image data for PSL system without using complicated 3D scaffold models. An effective Boolean operation based on VDF was utilized to improve the efficiency of geometrical manipulations required in the scaffold projection image generation. The design results demonstrated that the proposed algorithm can completely alleviate all the limitations and problems of the previous approaches mostly based on time-consuming and error-prone slicing process.

19 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20235
202217
202161
202099
2019112
201881