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Facial rejuvenation has driven a lot of research in the field of dermatology and plastic surgery, leading to many medical procedures. This paper proposes an age prediction method that could be used to better understand the ageing process and to evaluate the benefits of a rejuvenating treatment, for example. A supervised Facial Model (SFM) is built using Partial Least Squares regression (PLSR) to capture...
Wireless Capsule Endoscopy (WCE) is an endoscopy technology that allows medical personnel to view the digestive tract non-invasively. Physicians can detect diseases such as blood-based abnormalities, polyps, ulcers and Crohn's disease. In previous papers we have proposed methodologies that deal with such abnormalities. In the current paper we are proposing a novel approach to visualize the digestive...
In this paper, we introduce a novel approach based on higher order energy functions which have the ability to encode global structural dependencies to infer articulated 3D spine models to CT volume data. A personalized geometrical model is reconstructed from biplanar X-rays before spinal surgery in order to create a spinal column representation which is modeled by a series of intervertebral transformations...
Fast instance generation is a key requirement in atlas-based registration and other problems that need a large number of atlas instances. This paper describes a new method to represent and construct intensity atlases. Both geometry and intensity information are represented using B-spline deformation lattices; intensities are approximated using the multi-level B-spline approximation algorithm during...
The geometric shape of the human cerebral cortex is characterized by its complex and variable folding patterns. This pattern can be described at different scales from local scale such as curvature to global scale such as gyrification index or spherical wavelet. This paper presents a parametric folding pattern descriptor at the meso-scale of a cortical surface patch. The patch is represented by Bezier...
A computational framework is presented for 3-D liver shape approximation and characterization in order to determine the accuracy of shape reconstruction via Spherical Harmonics expansion. Spherical Harmonics is a powerful mathematical tool for expanding the shape. But in medical domain, livers have very variation geometry, in shape, size, and volume. In this regards, we evaluated and optimized the...
Statistical shape model (SSM) is to model the shape variation of an object. The statistical shape models are constructed by analysis of the positions of a set of landmark points based and use the surface information. In this paper, we propose a new PCA based statistical shape modeling technique and its application to medical applications. In the proposed method, boundary points of each slice are used...
Video-based tracking of contours on the human body has been shown to be useful for many applications, including gait and gesture recognition, posture estimation, and activity analysis. We present a contour tracking method that incorporates a novel edge feature and fuzzy contour template. We apply our method in tracking the motions of older adults exercising in a gym environment. The output of our...
Spherical harmonics are commonly used in the construction of multi-resolution representations of complex spherical shapes such as brain surface meshes. A key step in generating such representations for a spherical mesh is to construct a one-to-one map onto a sphere. A parametrization inevitably introduces local distortions such as stretching and compression, so that some regions can be severely undersampled...
This paper presents a novel approach for rehabilitation of the collapsing femoral head caused by ANFH from computer tomography (CT) images based on 3D statistical shape model. The shape knowledge about the biological variability of anatomical objects is fundamental for statistical shape analysis and discrimination between healthy and pathological structures. So we integrate the variability of an object...
In this paper, we propose a novel predictive model for object boundary, which can integrate information from any sources. The model is a dynamic ldquoobjectrdquo model whose manifestation includes a deformable surface representing shape, a volumetric interior carrying appearance statistics, and an embedded classifier that separates object from background based on current feature information. Unlike...
This paper proposes a novel technique to describe the shapes of women breasts in a low dimensional parameter space. The parameterization is obtained applying Principal Component Analysis (PCA) to a data set of about 40 Nuclear Magnetic Resonances of female breasts taken in a prone position. The resulting principal modes may be used as clinical indicator and have a direct medical interpretation.
Segmentation of the left ventricle (LV) is a hot topic in cardiac magnetic resonance (MR) images analysis and still remains an open issue. In this paper, we propose a novel method, radial B-Snake model based on improved gradient vector flow (GVF), to segment LV automatically. Due to the left ventriclepsilas circle-like shape prior in short-axis view, the region of interest (ROI) of LV could be transformed...
2D electrophoresis is a well known method for protein separation which is extremely useful in the field of proteomics. Each spot in the image represents a protein accumulation and the goal is to perform a differential analysis between pairs of images to study changes in protein content. It is thus necessary to register two images by finding spot correspondences. Although it may seem a simple task,...
An intelligent computer-aided diagnostics system may be developed to assist the radiologists to recognize the masses/lesions appearing in breast in different groups of benignancy/malignancy. In present work we have attempted to develop a computer assisted treatment planning system implementing Genetic algorithm-based Neuro-fuzzy approaches. The boundary based features of the tumor lesions appearing...
In this paper, a multiplatform computing tool for left ventricle (LV) motion analysis from three-dimensional cardiac images is described. The tool uses as input data, LV geometric representations constructed from multislice computed tomography databases, and LV 3D models reconstructed from biplane angiography projections. A non-rigid bidimensional correspondence algorithm is used to track a set of...
In this paper, we present a method for extracting center axis representations of tubular shapes obtained from medical images. The method extracts centerlines by computing minimum-cost paths from a graph based optimization algorithm which minimizes responses obtained from multi-scale medialness filters. These filters are designed from the assumption that tubular structures, in general, has circular...
We introduce a locally defined shape-maintaining method for interpolating between corresponding oriented samples (vertices) from a pair of surfaces. We have applied this method to interpolate synthetic data sets in two and three dimensions and to interpolate medially represented shape models of anatomical objects in three dimensions. In the plane, each oriented vertex follows a circular arc as if...
Training a shape prior has been potent scheme for anatomical object segmentations, especially for images with noisy or weak intensity patterns. When the shape representation lives in a high dimensional space, principal component analysis is often used to calculate a low dimensional variation subspace from frequently limited number of training samples. However, the eigenmodes of the sub-space tend...
We present a novel three dimensional (3D) region-based hidden Markov model (rbHMM) for unsupervised image segmentation. Our contributions are twofold. First, our rbHMM employs a more efficient representation of the image than approaches based on a rectangular lattice or grid; thus, resulting in a faster optimization process. Second, our proposed novel tree-structured parameter estimation algorithm...
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