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We present an on-line list-mode image reconstruction system using GPUs for a surgical PET imaging probe system. We used the nVidia GeForce 9800GTX+ and CUDA to reconstruct images. The proposed system can generate a three-dimensional image from simulated data in 70 msec. We also compared the processing time with respect to the number of LORs per subset. We are working on optimizing the CUDA code to...
Time-of-flight (TOF) PET scanners provide the potential for significantly improved signal-to-noise ratio (SNR) and lesion detectability in clinical PET. Therefore, it is likely that TOF will become the standard for clinical whole body PET in the near future. However, fully 3D TOF PET image reconstruction is a challenging task due to the huge data size. One solution to this problem is to rebin TOF...
Bolus tracking of contrast agent with MRI is a well established technique for measurement of local cerebral hemodynamic parameters flow, volume and mean transit time. When performed on a voxel-by-voxel basis, it allows development of hemodynamic parameter maps useful for assessment of ischemic damage following stroke and tumor characterization in cancer. The analysis of the acquired dynamic data requires...
A two-and-a-half-dimensional (2.5D) quantitative millimeter wave imaging algorithm, based on Newton-type optimization, is presented. The goal is to reconstruct the complex permittivity of a long inhomogeneous (lossy) scatterer, embedded in free space, from a number of time-harmonic scattered field measurements. This 2.5 D technique exploits the two-dimensional nature of the scatterer, while safeguarding...
We propose a novel method, fMRI-informed regional estimation (FIRE), which utilizes information from fMRI in E/MEG source reconstruction. FIRE takes advantage of the spatial alignment between the neural and the vascular activities, while allowing for substantial differences in their dynamics. Furthermore, with the regional approach, FIRE can be efficiently applied to a dense grid of sources. Inspection...
Current state-of-the-art image-based scene reconstruction techniques are capable of generating high-fidelity 3D models when used under controlled capture conditions. However, they are often inadequate when used in more challenging outdoor environments with moving cameras. In this case, algorithms must be able to cope with relatively large calibration and segmentation errors as well as input images...
We present a novel technique for calibrating display-camera systems from reflections in the user's eyes. Display-camera systems enable a range of vision applications that need controlled illumination, including 3D object reconstruction, facial modeling and human computer interaction. One important issue, though, is the geometric calibration of the display, which requires additional hardware and tedious...
This paper presents a novel approach to achieve accurate and complete multi-view reconstruction of dynamic scenes (or 3D videos). 3D videos consist in sequences of 3D models in motion captured by a surrounding set of video cameras. To date 3D videos are reconstructed using multiview wide baseline stereo (MVS) reconstruction techniques. However it is still tedious to solve stereo correspondence problems:...
Underwater video systems have assumed an increasingly important role in exploration and survey of the unknown deep ocean environments. This paper presents a real-time underwater video compression system that can be mounted on autonomous underwater vehicles (AUVs) for underwater survey applications. The hardware system is based on the digital media processor TMS320DM642 (DM642) of Texas Instruments,...
The observations in many applications consist of counts of discrete events, such as photons hitting a detector, which cannot be effectively modeled using an additive bounded or Gaussian noise model, and instead require a Poisson noise model. As a result, accurate reconstruction of a spatially or temporally distributed phenomenon (f) from Poisson data (y) cannot be accomplished by minimizing a conventional...
Panoramic stitching of static and dynamic scenes is a very important and challenging research area. For static scenes, number of approaches has been proposed so far. The result produced by these approaches provides great similarity between resultant panorama and input images with almost zero seam visibility. However for dynamic scenes, we have found that existing approaches are unable to overcome...
Digital close-range photogrammetry has been used increasedly in various engineering projects. By using digital cameras along with image processing, camera calibration and bundle adjustment method, measurements with high precision can be achieved. Based on analyzing the characteristics of 3D measurement for large workpiece and its actual demand, a procedure of reconstructing marked points is proposed...
We consider optimal resource allocation for wireless video sensors (WVSs), including the image sensor subsystem into the system analysis. By assigning a power-rate-distortion (P- R-D) characteristic for the image sensor, we build a comprehensive P-R-D framework for WVS optimization. Within the scope of the developed framework, we solve the problem of how to allocate power among the image sensor, compression,...
Reconstruction depth from 2D images is an important research issue in computer vision, and depth from defocus (DFD) is an effective way which takes the blurred degree of the region images whose depth of field is limit as the tool of computing depth. Now though there are many DFD methods, they all need to change camera parameters in order to attain blurred images, such as the focal length of the lens,...
This article presents a global optimization approach to reconstruct surfaces from a single document image. Instead of assuming globally developable in previous works which restricted the surface to be cylindrical, conical, etc, we use a free form parametric model which is simple yet expressive enough in the reconstruction task. We then apply developable constraints locally on sample points from extracted...
Independent component analysis (ICA) is a statistical technique where the goal is to represent a set of random variables as a linear transformation of statistically independent component variables. This paper proposes a new extended model for CT medical image de-noising, which is using independent component analysis and dynamic fuzzy theory. Firstly, a random matrix was produce to separate the CT...
We propose a novel framework to reconstruct the left ventricle (LV)'s 3D surface from sparse tagged-MRI (tMRI). First we acquire an initial surface mesh from a dense tMRI. Then landmarks are calculated both on contours of a specific new tMRI data and on corresponding slices of the initial mesh. Next, we employ several filters including global deformation, local deformation and remeshing to deform...
In systems like SPECT, raw data is obtained by the imaging system and then reconstructed and viewed by a human observer. We compare two approaches to optimizing SPECT for a detection task with a known signal in a statistically varying background. In a sequential approach, we optimize the collimator using an ideal observer applied to the sinogram. We then optimize the regularization of the reconstruction...
Automated tracking of fluorescent particles in living cells is vital for subcellular stoichoimetry analysis. Here, a new automatic tracking algorithm is described to track multiple particles, based on minimal path optimization. After linking feature points frame-by-frame, spatio-temporal data from time-lapse microscopy are combined together to construct a transformed 3D volume. The trajectories are...
Given the rapid growth in computational requirements for medical image analysis, Graphics Processing Units (GPUs) have begun to be utilized to address these demands. But even though GPUs are well-suited to the underlying processing associated with medical image reconstruction, extracting the full benefits of moving to GPU platforms requires significant programming effort, and presents a fundamental...
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