Search results for "Iterative reconstruction"
showing 10 items of 129 documents
Algorithms for Image Reconstruction
2010
Three-dimensional (3D) imaging is becoming one of the most important applications of radioactive materials in medicine. It offers good spatial resolution, a 3D insight into the human body, and a high sensitivity in the picomolar range because markers for biological processes can be detected well when labeled with radioactive materials. In addition, the technical equipment has undergone many technological achievements. This is true for single-photon emission computed tomography (SPECT), positron emission tomography (PET), and X-ray computed tomography (CT), which is often used in connection with the nuclear medical imaging systems, as also described in chapter 5 about sources in nuclear medi…
MRI resolution enhancement using total variation regularization
2009
We propose a novel method for resolution enhancement for volumetric images based on a variational-based reconstruction approach. The reconstruction problem is posed using a deconvolution model that seeks to minimize the total variation norm of the image. Additionally, we propose a new edge-preserving operator that emphasizes and even enhances edges during the up-sampling and decimation of the image. The edge enhanced reconstruction is shown to yield significant improvement in resolution, especially preserving important edges containing anatomical information. This method is demonstrated as an enhancement tool for low-resolution, anisotropic, 3D brain MRI images, as well as a pre-processing …
A wavelet-based demosaicking algorithm for embedded applications
2010
This paper presents an alternative to the spatial reconstruction of the sampled color filter array acquired through a digital image sensor. A demosaicking operation has to be applied to the raw image to recover the full-resolution color image. We present a low-complexity demosaicking algorithm processing in the wavelet domain. Produced images are available at the output of the algorithm either in the spatial representation or directly in the wavelet domain for high-level post processing in the latter domain. Results show that the computational complexity has been lowered by a factor of five compared to state of the art demosaicking algorithms.
Non-Homogeneity of Lateral Resolution in Integral Imaging
2013
We evaluate the lateral resolution in reconstructed integral images. Our analysis takes into account both the diffraction effects in the image capture stage and the lack of homogeneity and isotropy in the reconstruction stage. We have used Monte Carlo simulation in order to assign a value for the resolution limit to any reconstruction plane. We have modelled the resolution behavior. Although in general the resolution limit increases proportionally to the distance to the lens array, there are some periodically distributed singularity planes. The phenomenon is supported by experiments.
Geometrical super resolved lensless imaging
2011
In the field of super resolution researchers are trying to overcome both the diffraction as well as the geometrical bounds of an imaging system. In this paper we present a recently developed approach that aims to overcome the geometrical bounds while using a unified spatial light modulator (SLM) based lensless configuration.
Near field retrieval from far field using PDFT
2008
A new algorithm is applied for obtaining the near field form far field measurements. It is not only the simple DFT applied to the spectrum, but also a newer algorithm, called PDFT, which makes use of the information in the transformed domain. Its main advantage is that the resolution obtained is better than with DFT, since more information about the antenna is used. Furthermore, no iterations are applied and the best approximation in the way of minimum weighted norm is achieved.
Compensation of missing wedge effects with sequential statistical reconstruction in electron tomography.
2014
Electron tomography (ET) of biological samples is used to study the organization and the structure of the whole cell and subcellular complexes in great detail. However, projections cannot be acquired over full tilt angle range with biological samples in electron microscopy. ET image reconstruction can be considered an ill-posed problem because of this missing information. This results in artifacts, seen as the loss of three-dimensional (3D) resolution in the reconstructed images. The goal of this study was to achieve isotropic resolution with a statistical reconstruction method, sequential maximum a posteriori expectation maximization (sMAP-EM), using no prior morphological knowledge about …
Three dimensional reconstruction of intracoronary ultrasound images: roadmapping with simultaneously digitised coronary angiograms
2002
Three dimensional reconstruction of intracoronary ultrasound images offers a better appreciation of the axial relationship of vessel features and permits volumetric assessment, both of which depend critically on the spatial accuracy of the technique. This in turn is dependent on precise longitudinal orientation of the transducer in the vessel. The authors have developed a system which utilises simultaneously digitised fluoroscopic tracking of the radio-opaque transducer to orient the corresponding 2D ICUS images. This system may offer improved spatial accuracy of the three dimensional reconstruction and a means of precise identification of the 2D ICUS image which corresponds with a selected…
Deep Non-Line-of-Sight Reconstruction
2020
The recent years have seen a surge of interest in methods for imaging beyond the direct line of sight. The most prominent techniques rely on time-resolved optical impulse responses, obtained by illuminating a diffuse wall with an ultrashort light pulse and observing multi-bounce indirect reflections with an ultrafast time-resolved imager. Reconstruction of geometry from such data, however, is a complex non-linear inverse problem that comes with substantial computational demands. In this paper, we employ convolutional feed-forward networks for solving the reconstruction problem efficiently while maintaining good reconstruction quality. Specifically, we devise a tailored autoencoder architect…
Real-time computation of parameter fitting and image reconstruction using graphical processing units
2016
Abstract In recent years graphical processing units (GPUs) have become a powerful tool in scientific computing. Their potential to speed up highly parallel applications brings the power of high performance computing to a wider range of users. However, programming these devices and integrating their use in existing applications is still a challenging task. In this paper we examined the potential of GPUs for two different applications. The first application, created at Paul Scherrer Institut (PSI), is used for parameter fitting during data analysis of μ SR (muon spin rotation, relaxation and resonance) experiments. The second application, developed at ETH, is used for PET (Positron Emission T…