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The demand for automation in medical analysis is continuously growing with large number of application in biotechnology and medical research. Feature extraction and image matching are important steps in analyzing medical cells. In this research paper, we are concentrating on extracting and matching features from a full 3D volume data of lung cancer cell that was recorded with a confocal laser scanning...
In order to extract the medial axes of vascular objects from 3D medical volume data, a precise centerline extraction algorithm is proposed. A binary image sequence which has been segmented is taken as the input data. Distance transform is performed for the data to generate a distance map. Based on the distance map and for each target-voxel which belongs to the cavity of vascular structure, a Hessian...
A new method for visualisation and segmentation of vessel structures in 3D magnetic resonance angiography (MRA) images is presented. This method uses a simple statistical model of the information stored along parallel rays within the data set to derive a 2D projection image. Although similar to the maximum image projection (MIP) method, the new method uses a single parameter to achieve a higher contrast-to-noise...
Many medical image segmentation techniques have been proposed by lots of authors but they are mainly dedicated to particular solutions. There is no generic method for solving the image segmentation problem. The difficulty comes from that two types of noise are presented in medical images: physical noise due to the acquisition system, for example, Optical, X-rays and MRI, and physiological noise due...
Marching cube algorithm is a classical 3D reconstruction method, while topological ambiguity exists. Marching tetrahedra algorithms can solve the problem of topological ambiguity, but there are too many triangle patches. This paper proposes a new decomposing method that combines with MC method. We used several sets of medical images in the experiments, which proved this method could avoid topological...
Extracting hepatic vasculature from three dimensional imagery is important for diagnosis of liver disease and planning of liver surgery. In this paper we propose a method for generation of 3D skeletal graph of liver vessels using thinning algorithm and graph theory. First of all, basic methodology in the proposed method is introduced. Secondly, the skeletonization method together with a pre-processing...
Remote training is one of the rapid growing fields in computer applications. This paper will investigate the pivot technologies in remote training, specifically for remote control or operational training. By means of working with a test platform of robot telecontrol, the pivot technologies in remote operational training are identified, which could be propagate to the general training scenario, such...
A major source of error in the analysis of functional Magnetic Resonance images is the presence of spurious activation arising on account of patient head movement at the time of image acquisition. This makes it imperative for the images to be subjected to motion correction through registration. A number of solutions to the problem currently do exist though there is always the need for faster approaches...
In this paper we develop a new approach of analyzing 3D shapes based on the eigen-system of the Laplace-Beltrami operator. While the eigenvalues of the Laplace-Beltrami operator have been used previously in shape analysis, they are unable to differentiate isospectral shapes. To overcome this limitation, we propose here a new signature based on nodal counts of the eigenfunctions. This signature provides...
We address the difficult problem of segmenting the inflamed synovial tissue in multi-modal 3D MR sequences of the wrist. The complex morphology of the structures to segment, the dimensionality of the images, and the multiple modalities all contributes to the difficulty of the problem. We propose a solution based on a voxel classifier built on relatively few features selected from a large pool computed...
Various cortical measures such as cortical thickness are routinely computed along the vertices of cortical surface meshes. These metrics are used in surface-based morphometric studies. If one wishes to compare the surface-based morphometric studies to 3D volume-based studies at a voxel level, 3D interpolation of the sparsely sampled 2D cortical data is needed. In this paper, we have developed a new...
In this paper, it is provided to reconstruct three-dimensional(3D) models of human body by using CT slices and digital images and precisely finding locations of pathological formations such as tumours. 3D image CT reconstruction is an attractive field generally in digital image processing techniques, especially in biomedical imaging. It is necessary to incise a 3D object to obtain detail structure...
The aim of this work is to segment, and quantify, the vasculature of tumours, based on fluorescent microscope 3D images. Such images have poor contrast and the vascular features vary substantially within a 3D volume. In this paper, we introduce a method to estimate local phase in 3D images based on the monogenic signal theory, and illustrate its performance on our vasculature images.
In this paper a stepwise approach is described for the quantitative solution of 3D inverse scattering problems in which one performs a preliminary estimation of the support of the targets. Such an approach is assessed on some experimental data provided by the Institut Presnel of Marseille, France .
Accurate liver segmentation on computed tomography (CT) images is a challenging task because of inter and intra- patient variations in liver shapes, similar intensity with its nearby organs. We proposed a liver segmentation method based on region growing approach. First of all, basic theory of region growing approach is introduced. Secondly, a pre-processing method using anisotropic filter and Gaussian...
In diagnosing pulmonary diseases aided by computer, accurate segmentation of the airway tree from the CT images is the basis for subsequent processing and analyzing. It is still a challenging task due to the image noise, partial volume effect and texture similarity of the airway and parenchyma. In order to solve these problems, various algorithms have been proposed, among which the region growing...
In this paper we introduce a novel algorithm for alignment of Electron Microscopy images for 3D reconstruction. The algorithm extends the Expectation Maximization - Iterative Closest Points (EM-ICP) algorithm to go from point matching to patch matching. We utilize local patch characteristics to achieve improved registration. The method is applied to enable 3D reconstruction of Transmission Electron...
This paper presents a novel method for the interactive identification of contextual interest points within volumetric data by picking on a direct volume rendered image. In clinical diagnostics the points of interest are often located in the center of anatomical structures. In order to derive the volumetric position which allows a convenient examination of the intended structure, the system automatically...
The analysis of Hepatic Portal Vein (HPV) is important in liver surgical planning and diseases diagnosis, such as living-related liver transplant and oncologic resections. Skeletonization is always the necessary way for vasculature quantification analysis. In this paper, we presented an automatic skeletonization algorithm for 3D HPV based on 3D topological thinning. Since the topological thinning...
This paper presents a supervised statistical-based cerebrovascular segmentation method from time-of-flight MRA. The novelty of this method is that rather than model the dataset over the entire intensity range, we at first use a low threshold to eliminate the lowest intensity region, and then use two uniform distributions to model the middle and high intensity regions, respectively. Subsequently, in...
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