Statistical shape modeling is a widely used technique for the representation and analysis of the shapes and shape variations present in a population. A statistical shape model models the distribution in a high dimensional shape space, where each shape is represented by a single point. We present a design study on the intuitive exploration and visualization of shape spaces and shape models. Our ...

Monte Carlo simulation is a very powerful tool in understanding performances of positron tomographs as well as in assessing image reconstruction algorithms and their implementations. We present an object-oriented Monte Carlo simulator developed for 3D positron tomography. Results from phantom simulation studies including absorption and scattering of the photons in the field-of-view are presente...

For a sample of 51 blazars with extensive optical polarization data, we used circular statistics to calculate the scatter among the polarization position angles for each object. We found that this scatter is correlated with the radio core dominance. We compared this relationship with the predictions of a simple transverse shock model. The result suggests that blazar jets are likely to cover a w...

A Monte Carlo simulation, based on GEANT4, has been developed to compute the contribution of first-order, second-order, and higher order scattering in a Computed Tomography (CT) system equipped with an industrial 450 kV X-ray tube and an area detector. The validation of simulation against the experimental data showed a good agreement. The amount of scattering produced by several hollow aluminum...

In this paper we present a scatter correction method for a regularized list mode maximum likelihood reconstruction algorithm for the positron emission mammograph (PEM) that is being developed at our laboratory. The scatter events inside the object are modelled as additive Poisson random variables in the forward model of the reconstruction algorithm. The mean scatter sinogram is estimated using ...

Multi-dimensional Visual Tracking (MVT) problems include visual tracking tasks where the system state is defined by a high number of variables corresponding to multiple model components and/or multiple targets. A MVT problem can be modeled as a dynamic optimization problem. In this context, we propose an algorithm which hybridizes Particle Filters (PF) and the Scatter Search (SS) metaheuristic,...

Fully three-dimensional (3D) positron emission tomography (PET) can achieve high sensitivity of coincidence events, but the absence of inter-slice septa inevitably leads to increased scattered events. The scattered events can represent as much as 50% of the total detected events. In this research, we proposed a scatter correction method for 3D PET based on beam stoppers and dual-energy window a...

The purpose of this study was to develop and evaluate the hybrid scatter correction algorithm (HSC) for CT imaging. Therefore, two established ways to perform scatter correction, i.e. physical scatter correction based on Monte Carlo simulations and a convolution-based scatter correction algorithm, were combined in order to perform an object-dependent, fast and accurate scatter correction. Based...

The purpose of this study is to investigate the use of hyperspectral X-ray imaging i.e, an imaging modality where spectral information on detected X-rays is available, for the removal of scatter in mammography. Features that suggest the presence of cancer are often low in contrast or small in size and therefore a good image quality is required in order to locate them. Current mammography system...

ID: 14214 Title: A novel scatter reduction and correction method to improve cone-beam CT (CBCT) image quality Purpose: To develop a novel scatter reduction and correction method to improve the CBCT image quality for IGRT applications. Method and Materials: A one-dimensional grid composed of lead with equal interspacing was positioned between the x-ray source and the imaging object during CBCT a...