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A new graph-based approach for simultaneous segmentation of lungs in 4D CT scans is presented. The approach is based on a “just enough” user interaction principle and consists of two stages. First, a fully automated graph-based segmentation algorithm is applied. Second, the user inspects the result and can correct local segmentation errors with all interactions performed within the graph-based computer-aided...
This paper presents a novel 3D segmentation framework for structures with spatially varying boundary properties, such as the hippocampus (HC). The proposed method is based on Active Contour Models (ACMs) built on top of the multi-atlas concept. We propose the incorporation of an Adaptive Gradient Distibution on the Boundary map (AGDB) into the ACM framework. AGDB, by being adapted to the evolving...
We propose a shape-based approach for the segmentation of the left ventricle (LV) wall on cardiac first-pass magnetic resonance imaging (FP-MRI) using level sets. To reduce the variabilities of the LV wall in FP-MRI, it is first imperative to co-align the time series images to account for the global and local motions of the heart. Therefore, we developed a two-step registration methodology that includes...
The standard approach in interventional treatment of atrial fibrillation (AFib) is pulmonary vein isolation (PVI). PVI can be achieved by placing radio-frequency (RF) lesions contiguously around the pulmonary veins attached to the left atrium. Since accurate lesion placement may be difficult, pre-planned ablation lines can be used for better navigation both when using mapping systems or also when...
We introduce a 3D model-based approach for automatic segmentation of 3D fluorescent heterochromatin foci from microscopy images. The approach employs a new 3D parametric intensity model based on a spherical harmonics (SH) expansion and can represent foci of regular and highly irregular shapes. By solving a least-squares minimization problem, the new model is directly fitted to the 3D image data, and...
Planning radiotherapy of prostate cancer requires the prostate segmentation in computed tomography (CT) images that can be manual (done by medical doctors), semi-automatic or automatic. Additional usage of magnetic resonance (MR) images, where the soft tissue are better visible, makes this operation more robust. The paper addresses the problem of prostate segmentation in MR data. Its main contribution...
Automatic classification of figures present in healthcare documents is known to be useful for biomedical document mining. The context of a document is directly reflected in the figures present within them. Embedded text within these figures along with image features have been used for figure retrieval. We demonstrate that image features based on structural properties of figures alone is sufficient...
This paper proposes Tablet counter machine base on image processing. A digital webcam creates an image of drug being dispensed. This image is displayed in standard RGB model. The original image will change to grayscale image. Then grayscale image will filtered for noise using a median filter and then using threshold we obtain a digital binary image of the pill being dispensed. The image is further...
This paper proposes a cartilage thickness detection and visualization method that does not utilize a shape model. The proposed method consists of three parts: volume of interest (VOI) initialization, bone segmentation, and cartilage thickness visualization. For VOI initialization, a novel 3D U-shape cuboidal filter is proposed to detect individual bones such as the femur, tibia, and patella, and for...
The segmentation of shapes from biomedical images has a wide range of uses such as image based modelling and bioimage analysis. In this paper, an active contour model is proposed for the segmentation of N-dimensional biomedical images. The proposed model uses a curvature smoothing flow and an image attraction force derived from the interactions between the geometries of the active contour model and...
To inspect medical capsules with one-dose package (ODP), we propose an automated inspection system based on computer vision. In the proposed system, we capture both-side of capsules at once and apply hierarchical recognition. In this paper, we report several results of preliminary experiments, which distinguish 9 kinds of capsules. As a result, we have achieved 99.1 percent recognition rate and discuss...
In this paper, we propose a new surface-based method to solve the rotation transformation of 3D rigid registration. Different from the criterion that minimize the sum of the squares of the errors between the corresponding parts of objects, here we estimate the spatial modalities of objects by their orientations. In details, Gauss map of surface is introduced to measure the distribution of surface...
The fundamental step to get a Statistical Shape Model (SSM) is to align all the training samples to the same spatial modality. In this paper, we propose a new 3D alignment method using surface parameterization theory to solve the rotation transformation of 3D rigid registration. It is a feature based alignment method which matches two models depending on comparing the distribution of spherical conformal...
The vertical Cup-to-Disc Ratio (CDR) is an important indicator in the diagnosis of glaucoma. Automatic segmentation of the optic disc (OD) and optic cup is crucial towards a good computer-aided diagnosis (CAD) system. This paper presents a statistical model-based method for the segmentation of the optic disc and optic cup from digital color fundus images. The method combines knowledge-based Circular...
Active Contour Models have been widely used in computer vision for segmentation purposes, while anatomically constrained ACMs have offered a valuable solution on medical image segmentation. Efforts have been devoted on various ways of modeling prior knowledge. This paper focuses on how to efficiently incorporate prior knowledge, into an ACM evolution framework, using the structures' distribution map...
With the rapid development of medical imaging technologies, images, and especially digital images, are produced in ever-increasing quantities and more and more important in diagnostics and therapy. This article proposes a retrieval methodology based on multi-feature for CT images of chest scan. Experiments on 1000 CT images of chest scan demonstrate that retrieval based on multi-feature together with...
This paper proposes a new descriptor for radiological image retrieval. The proposed approach is based on fuzzy shape contexts, Fourier transforms and Eigenshapes. At first, fuzzy shape context histograms are computed. Then, a 2D FFT is performed on each 2D histogram to achieve rotation invariance. Next, histograms are projected onto a lower dimensionality feature space. The new space is more representative...
An automatic segmentation method for extraction of human rib structures from chest CT volume data is presented. Segmentation is initiated from the middle coronal slice to attain complete and isolated 12 pairs of ribs with a recursive tracking on coronal slices spreading from the middle coronal slice. At each coronal slice, the lung contours are extracted, candidate rib regions are derived from thresholding,...
Morphology of bones, teeth, and some particular structures are widely used for categorizing species and studying their evolution. In this paper, we used groupwise registration to provide a representative image from the set of the image samples that represents its typical morphology. We also provided perturbation map which indicates the deviation of each point through the ensemble. These images support...
We consider the problem of processing high angular resolution diffusion images described by orientation distribution functions (ODFs). Prior work showed that several processing operations, e.g., averaging, interpolation and filtering, can be reduced to averaging in the space of ODFs. However, this approach leads to anatomically erroneous results when the ODFs to be processed have very different orientations...
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