Marcin Janaszewski

Hole filling in 3D volumetric objects

The construction of hole filling (or hole segmentation) method for 3D volumetric images is a new challenging issue in computer science. It needs a geometrical approach since from a topological point of view 3D holes (tunnels) are not well-delimited subsets of three dimensional space. In this paper, the authors propose an original, efficient, flexible algorithm of hole filling for volumetric objects. The algorithm has been tested on artificial objects and very complicated crack propagation tomography images. The qualitative results, quantitative results and features of proposed approach are presented in the paper. According to our knowledge it is the first algorithm of hole filling for volumetric objects.

Reliable Airway Tree Segmentation Based on Hole Closing in Bronchial Walls

Reliable segmentation of a human airway tree from volumetric computer tomography (CT) data sets is the most important step for further analysis in many clinical applications such as diagnosis of bronchial tree pathologies. In this paper the original airway segmentation algorithm based on discrete topology and geometry is presented. The proposed method is fully automated, reliable and takes advantage of well defined mathematical notions. Holes occur in bronchial walls due to many reasons, for example they are results of noise, image reconstruction artifacts, movement artifacts (heart beat) or partial volume effect (PVE). Holes are common problem in previously proposed methods because in some areas they can cause the segmentation algorithms to leak into surrounding parenchyma parts of a lung. The novelty of the approach consists in the application of a dedicated hole closing algorithm which closes all disturbing holes in a bronchial tree. Having all holes closed the fast region growing algorithm can be applied to make the final segmentation. The proposed method was applied to ten cases of 3D chest CT images. The experimental results showed that the method is reliable, works well in all cases and generate good quality and accurate results.

3D inspection of fabrication and degradation processes from X-ray (micro) tomography images using a hole closing algorithm

This paper presents relatively new examples of X-ray tomography applications to engineering materials. These examples illustrate the usefulness of the technique to inspect fabrication processes, but also to study degradation processes that may occur during service, for example from corrosion. It also shows how advanced image processing algorithms such as the hole closing method, can be used to extract features, or correct processed images.

Geometric Approach to Hole Segmentation and Hole Closing in 3D Volumetric Objects

Hole segmentation (or hole filling) and hole closing in 3D volumetric objects, visualised in tomographic images, has many potential applications in material science and medicine. On the other hand there is no algorithm for hole segmentation in 3D volumetric objects as from the topological point of view a hole is not a 3D set. Therefore in the paper the authors present a new, geometrical approach to hole closing and hole filling in volumetric objects. Moreover an original and efficient, flexible algorithm of hole filling for volumetric objects is presented. The algorithm has been extensively tested on various types of 3D images. Some results of the algorithm application in material science for crack propagation analysis are also presented. The paper also includes discussion of the obtained results and the algorithm properties.

Robust algorithm for tunnel closing in 3D volumetric objects based on topological characteristics of points

Highlights? We propose a robust, linear in time modification of Aktouf et al. algorithm for tunnel closing in 3D volumetric objects. ? The studied algorithm is also a modification of tunnel closing algorithm (ITC) presented in the authors previous work. ? Proposed robust tunnel closing algorithm RTC outperforms ITC and the original Aktouf et al. proposition. ? RTC generates a tunnel closing patch which is insensitive to all kind of branches situated in the vicinity of the tunnel. In this letter, we propose a robust, linear in time modification of Aktouf, Bertrand and Perrotons algorithm for tunnel (3D hole) closing in 3D volumetric objects. Our algorithm is insensitive to small distortions and branches. The algorithm has been tested on various 3D images including very complicated 3D crack propagation images. The results of the tests, discussion of the algorithm properties and future research plans are also included in the paper.

Outer surface reconstruction for 3D fractured objects

We study surface reconstruction using a combination of anisotropic Gaussian filter and image segmentation technique -the minimum surface method. Anisotropic Gaussian filtering allows to manage a contrast between intensities of the discontinuity and the object in a desired direction. The minimum surface method detects properly outer boundaries even affected by boundary leakage in the vicinity of blurred edges. The algorithm is tested on a set of real 3D images of large corrosion cracks in stainless steel that initiated at the surface of the tested samples. Results are presented and discussed.

Airway Tree Segmentation from CT Scans Using Gradient-Guided 3D Region Growing

In this paper a new approach to CT based investigation of pulmonary airways is introduced. Especially a new - fully automated algorithm for airway tree segmentation is proposed. The algorithm is based on 3D seeded region growing. However in opposite to traditional approaches region growing is applied twice: firstly --- for detecting main bronchi, secondly --- for localizing low order parts of the airway tree. The growth of distal parts of the airway tree is driven by a map constructed on the basis of morphological gradient.

Comparison of Several Centreline Extraction Algorithms for Virtual Colonoscopy

In the paper, authors report on test of three skeletonization algorithms, which could be used as centreline generators for 3D colon images. Two of them belong to the topological thinning group of skeletonization algorithms and the last one to the distance mapping group. After adaptation to centreline generation task the algorithms were tested on a real 3D colon image and obtained results are reported along with the characteristics of each algorithm performance. What is more the authors have made some improvements to the algorithms in order to obtain better results. The improved algorithms were also tested and results are reported. Moreover the paper contains comparison of the new algorithms with their original counterparts. Final discussion and presentation of future works are also included in the paper.

Multistage Segmentation of Lamellae Colonies Based on Directional Filter Bank and PCA Analysis

Abstract This paper presents a new approach to segment heavily 3D textured images such as the one of lamellar titatnium alloys obtained from X-ray tomography. The presented method considers NSDFB and gradient from gray-level value to recognize directionality of structure in the image. Second level of classication is needed due to the high complexity of the titanium alloys structure. During the segmentation algorithm takes into account the interaction between objects.

New Algorithm for Modeling of Bronchial Trees

Abstract The article presents new conception of 3D model of human bronchial tubes, which represents bronchial tubes extracted from CT images of the chest. The new algorithm which generates new model is an extension of the algorithm (basic algorithm) proposed by Hiroko Kitaoka, Ryuji Takaki and Bela Suki. The basic model has been extended by geometric deformations of branches and noise which occur in bronchial trees extracted from CT images. The article presents comparison of results obtained with the use of the new algorithm and the basic one. Moreover, the discussion of usefulness of generated new models for testing of algorithms for quantitative analysis of bronchial tubes based on CT images is also included.