Original Volume Data Research Articles

Wavelet Decomposition-Based Approach for Fast Damage Detection of Civil Structures

This paper presents a method, which can be implemented under limited resources such as wireless sensor network devices, for damage detection of civil structures. The detection method is applied to transient waves from vibration responses, and it consists of Haar wavelet decomposition, thresholding, quantization, and differentiating metric. Before the differentiating metric, a target signal is compressed into the wavelet coefficients .signature.. The results indicate that a single measurement channel without time synchronization of other measurement points is effective for instant damage detection through the case study using the ASCE structural health monitoring (SHM) benchmark program. It is also shown that we can reduce the data to a small fraction of the original data volume using this method, while retaining enough information to detect structural damage and its severity. The approach illustrated in this paper implies a promise of wavelet-based data compression and analysis for the increasing volume of SHM data.

Combining 2D wavelet edge highlighting and 3D thresholding for lung segmentation in thin-slice CT

The first step in lung analysis by CT is the identification of the lung border. To deal with the increased number of sections per scan in thin-slice multidetector CT, it has been crucial to develop accurate and automated lung segmentation algorithms. In this study, an automated method for lung segmentation of thin-slice CT data is presented. The method exploits the advantages of a two-dimensional wavelet edge-highlighting step in lung border delineation. Lung volume segmentation is achieved with three-dimensional (3D) grey level thresholding, using a minimum error technique. 3D thresholding, combined with the wavelet pre-processing step, successfully deals with lung border segmentation challenges, such as anterior or posterior junction lines and juxtapleural nodules. Finally, to deal with mediastinum border under-segmentation, 3D morphological closing with a spherical structural element is applied. The performance of the proposed method is quantitatively assessed on a dataset originating from the Lung Imaging Database Consortium (LIDC) by comparing automatically derived borders with the manually traced ones. Segmentation performance, averaged over left and right lung volumes, for lung volume overlap is 0.983+/-0.008, whereas for shape differentiation in terms of mean distance it is 0.770+/-0.251 mm (root mean square distance is 0.520+/-0.008 mm; maximum distance is 3.327+/-1.637 mm). The effect of the wavelet pre-processing step was assessed by comparing the proposed method with the 3D thresholding technique (applied on original volume data). This yielded statistically significant differences for all segmentation metrics (p<0.01). Results demonstrate an accurate method that could be used as a first step in computer lung analysis by CT.

Development of a simple image viewer designed for small X-ray field CT equipment 3DX

To develop a simple image viewer that utilizes image files in general-purpose formats that are written from the original 3DX volume data. We used FLASH MX2004 for Macintosh to develop a simple image viewer. In developing the software for the simple image viewer, we decided that the viewer should provide the following features: (1) be available to both Windows OS and Mac OS, (2) allow interlocking of the 3D images, (3) display image enlargement, and (4) allow distance measurements. The accuracy of the distance measurements was evaluated. The procedure was as follows: (1) write 3D images in jpeg format to a folder on i-VIEW; (2) place the folder containing the 3D images into the directory of the simple image viewer software on a PC; (3) start the software and open the window to input the folder name containing the 3D images; and (4) display the 3D images. Our viewer had features such as image enlargement, interlocking 3D images, drawing, and distance measurements. No significant differences were shown between the measurements made by our simple viewer and the actual values of the images in any direction. Our image-viewing software for 3DX is beneficial for clinical use.

A102 ボリュームデータ検索用インデクスとしてのCPGの妥当性の検討

Nowadays, many large volume data sets have been generated from numerical simulations and digital measurements in various fields. Advances in computer and measurement device technologies have enabled their use in large-scale numerical simulations and high-resolution digital measurements, thus generating volume data which is continuously increasing in size and complexity. As a result, an efficient technique for a classification of and searching for these data sets is highly desired. Then, we developed the retrieval method that used critical point graph (CPG) as an index that compactly expressed the feature of the volume data. However, an enough examination was not done whether to approve the relation of one to one between CPG and original volume data. In this paper, we investigate whether another volume data that generates the same graph as CPG created from a certain voxel data with the scalar value of 1 byte exists, and examine the validity of CPG as the index for the retrieval.

Three-dimensional display and arbitrary region interactive segmentation of high-resolution virus capsids from cryo-electron microscopy single particle reconstruction

Recent advances in cryo-electron microscopy (cryo-EM) instrumentation and single particle reconstruction have created opportunities for high-throughput and high-resolution three-dimensional (3-D) structure determination of virus. In order to visualize and effectively understand the 3-D structure, we present a display method based on surface rendering, which has the function of 3-D arbitrary region interactive segmentation and quantitative analysis, and integrate them into a software package called CEM-3DVDSS (cryo-EM 3-D virus display and arbitrary region segmentation system). CEM-3DVDSS consists of a complete set of modular programs for 3-D display and segmentation of icosahedral virus, which is organized under a graphical user interface and provides user-friendly options. First, we convert volume data in the MRC format obtained by cryo-EM single particle reconstruction to the format of our own software; in the preprocessing step, the original volume data are compressed and a better vector dimension is found for controlling the speed and detail of display. Then, the new volume data can be displayed and segmented using CEM-3DVDSS. We demonstrate the applicability of CEM-3DVDSS by displaying the 3-D structures of 2.5 nm (resolution) BmCPV (Bombyx mori cytoplasmic polyhedrosis virus), 2.5 nm CSBV (Chinese Sacbrood bee virus) and 1.4 nm C6/36DNV (Densonucleosis virus). As a result, both the 3-D display speed and signal-to-noise ratio of CEM-3DVDSS are improved compared with the original method, and the segmentation results become precise and more intact with additional function of quantitative analysis of 3-D structure.

Q-guided wavelet-domain amplitude correction

This paper presents a novel way of treating seismic reflection amplitudes for transmission effects due to the overburden. The process has benefits for structural interpretation due to the improved visibility of events. Further processing of the data also benefits from a reduction in overburden-induced amplitude changes that can otherwise cause processing artefacts such as migration smiles. A wavelet transform decomposition of the data is used to derive local frequency, space and time varying gain factors from windows of seismic data. These are then constrained using a frequency-constant residual Q model in order to stabilise them against noise or other sources of estimation error. The resulting gain factors are applied to each wavelet voice and the data is reconstructed by an inverse wavelet transform. This is referred to as a Q-guided amplitude correction, as shorthand for the process of constraining the data-derived scalars by frequency-constant residual Q. A by-product of the process is that local estimates of relative Q are generated at the density of the original data volume, and can help with the overall interpretation of the data. Furthermore, once local amplitude variations have been removed, a coarsely sampled estimate of the background Q model can be used to compensate for any slowly varying amplitude and phase changes that exist throughout the survey area.

MR cholangiography 3D biliary tree automatic reconstruction system

An algorithm for reconstructing magnetic resonance cholangiography (MRC) biliary structure is proposed. The processing of MRC data can be divided into four phases. In the first phase, the region of interest (ROI) containing the liver and biliary ducts is extracted from the original volume data based on human anatomy and B-spline curve. The second phase involves segmenting the biliary ducts from the region identified in the previous phase. Because the image of biliary portion is brighter than the liver, the segmentation is started by choosing the brightest pixel in the ROI as the seed for 3D region growing. This procedure could be executed many times, depending on the provided stopping condition. In the third phase, the segmented biliary duct regions are traced to construct the biliary tree. An automated 3D tracking algorithm is proposed for this phase. This 3D tracking algorithm estimates the coordinates of the points along the medial axis of each biliary duct branch. The cross sections associated with the points along the medial axis are also calculated approximately during the tracking process. The biliary tree data structure is constructed in this phase. The biliary tree is reconstructed and rendered in the last phase. Although the proposed algorithm takes a longer time compared with the conventional approach, the reconstructed biliary tree 3D structure can provide more clearly image. A concise representation for the biliary tree can be achieved with the proposed method and provide both quantitative and structural information for clinical reference.

Modeling Shape and Topology of Low-Resolution Density Maps of Biological Macromolecules

In the present work we develop an efficient way of representing the geometry and topology of volumetric datasets of biological structures from medium to low resolution, aiming at storing and querying them in a database framework. We make use of a new vector quantization algorithm to select the points within the macromolecule that best approximate the probability density function of the original volume data. Connectivity among points is obtained with the use of the alpha shapes theory. This novel data representation has a number of interesting characteristics, such as 1) it allows us to automatically segment and quantify a number of important structural features from low-resolution maps, such as cavities and channels, opening the possibility of querying large collections of maps on the basis of these quantitative structural features; 2) it provides a compact representation in terms of size; 3) it contains a subset of three-dimensional points that optimally quantify the densities of medium resolution data; and 4) a general model of the geometry and topology of the macromolecule (as opposite to a spatially unrelated bunch of voxels) is easily obtained by the use of the alpha shapes theory.

Ventricular shape visualization using selective volume rendering of cardiac datasets

In this paper, we present a novel technique of improving volume rendering quality and speed by integrating original volume data and global model information attained by segmentation. The segmentation information prevents object occlusions that may appear when volume rendering is based on local image features only. Thus the presented visualization technique provides meaningful visual results that enable a clear understanding of complex anatomical structures. In the first part, we describe a segmentation technique for extracting the region of interest based on an active contour model. In the second part, we propose a volume rendering method for visualizing the selected portions of fuzzy surfaces extracted by local image processing methods. We show the results of selective volume rendering of left and right ventricle based on cardiac datasets from clinical routines. Our method offers an accelerated technique to accurately visualize the surfaces of segmented objects.

Automated segmentation and visualization of the pulmonary vascular tree in spiral CT angiography: an anatomy-oriented approach based on three-dimensional image analysis.

A new method for automated segmentation of the pulmonary vascular tree in spiral CT angiography was developed based on 3D image analysis techniques and anatomic knowledge. For efficient and effective segmentation, an anatomy-oriented approach was introduced, in which several anatomic structures are segmented sequentially and the properties of each segmented structure are used for the next step of segmentation and for validation of intermediate results. By use of clinical data of 12 patients, parameters for segmentation were analyzed and optimized. The effectiveness of the segmentation method was evaluated through the visual assessment by comparison between images of the segmentation results by volume rendering and images of maximum intensity projection of the original volume data.

Fast computation of isosurface contour spectra for volume visualization

Surface rendering and the construction of transfer functions for direct volume rendering are often based on thresholding and the resulting isosurfaces. Several approaches have been proposed to simplify the process of finding meaningful isosurface thresholds. However, optimal rendering parameters are determined in many approaches by analysis of the rendered images and not of the original volume data, thus requiring a cost-intensive thresholding/rendering optimization cycle. In this paper we present a time- and memory-efficient method for automated detection of meaningful intensity transitions between different tissue types to support visualization of CT volume data. In a single pass through the data volume a contour spectrum is determined which in particular indicates the total gradient integral of the isosurface for each possible threshold.

An efficient volume- rendering algorithm with an analytic approach

We present a new approach, analytic isosurface rendering, for volume rendering. The isosurface of a cell can be modeled as an analytic function, and the intersection between a ray and the isosurface can be computed directly. An octree structure efficiently searches the cells containing isosurfaces. The octree is easy to implement and can be stored in a compact form. It needs extra memory space - at most 27/64 of the size of the original data volume. Front-to-back projection can easily be implemented under the octree structure. A union-find-based algorithm maintains the frame buffer efficiently. Experimental results show that a volume rendering program with our approach is very efficient and maintains the quality of the rendered images.

Visualization of 3D volume data using an optical model

In this paper we propose a general model for the visualization of the 3D volume data, called optical model (OM). We present the model in its most general form, and a particular case is used for the display of computed tomography (CT) data. The optical model contains some of the techniques available in the literature as particular cases. It does not use ray tracing however it uses the wave characteristics of the light. Using Maxwell's equations and the boundary conditions, the equations involved in the visualization process take a simple form. The optical model proposes to use such optical concepts as reflection, transmission, diffusion, absorption, or a combination of them for the visualization of the volume data. This new model uses the normalized gradient as the normal to the surface where diffusion takes place. In the optical model the optical constants involved in the calculations are directly mapped from the original 3D volume data. The optical model is addressed to display any kind of 3D volume data, however we only applied it in the visualization of CT data, as a particular example.