Reducing the radiation dose in CT imaging has become an active research topic and many solutions have been proposed to remove significant noise streak artifacts reconstructed images. Most of these methods operate within domain image that is subject restoration. This, however, poses limitations on extent filtering possible. We advocate take into consideration vast body external knowledge exists already acquired medical images, since after all, this what radiologists do when they examine low...

Iterative algorithms have become increasingly popular in computed tomography (CT) image reconstruction, since they better deal with the adverse artifacts arising from low radiation dose acquisition. But iterative methods remain computationally expensive. The main cost emerges projection and back operations, where accurate CT system modeling can greatly improve quality of reconstructed image. We present a framework that improves upon one particular aspect - basis functions. It differs current...

Purpose: Acquiring data for CT at low radiation doses has become a pressing goal. Unfortunately, the reduced quality adversely affects of reconstructions, impeding their readability. In previous work, authors showed how prior regular‐dose scan same patient can efficiently be used to mitigate low‐dose artifacts. However, since is not always available, now extend authors’ method use database images other patients. Methods: The framework first matches (target) with in and then selects set that...

We describe a GPU-accelerated framework that efficiently models spatially (shift) variant system response kernels and performs forward- back-projection operations with these for the DIRECT (Direct Image Reconstruction TOF) iterative reconstruction approach. Inherent challenges arise from poor memory cache performance at non-axis aligned TOF directions. Focusing on GPU access patterns, we utilize different kinds of according to patterns in order maximize performance. also exploit...

Due to the sheer volume of data it is typically impractical analyze detailed performance an HPC application running at-scale. While conventional small-scale benchmarking and scaling studies are often sufficient for simple applications, many modern workflow-based applications couple multiple elements with competing resource demands complex inter-communication patterns which cannot easily be studied in isolation at small scale. This work discusses Chimbuko, a analysis framework that provides...

Color mapping and semitransparent layering play an important role in many visualization scenarios, such as information volume rendering. The combination of color transparency is still dominated by standard alpha-compositing using the Porter-Duff over operator which can result false colors with deceiving impact on visualization. Other more advanced methods have also been proposed, but problem far from being solved. Here we present alternative to these existing specifically devised avoid...

Ptychography is an emerging imaging technique that able to provide wavelength-limited spatial resolution from specimen with extended lateral dimensions. As a scanning microscopy method, typical two-dimensional image requires number of data frames. diffraction-based technique, the real-space has be recovered through iterative reconstruction algorithms. Due these two inherent aspects, ptychographic generally computation-intensive and time-consuming process, which limits throughput this method....

Multi-slice X-ray ptychography offers an approach to achieve images with a nanometre-scale resolution from samples thicknesses larger than the depth of field imaging system by modeling thick sample as set thin slices and accounting for wavefront propagation effects within specimen. Here, we present experimental demonstration that resolves two layers nanostructures separated 500 nm along axial direction, sub-10 sub-20 resolutions on layers, respectively. Fluorescence maps are simultaneously...

Statistical iterative reconstruction (SIR) algorithms have shown great potential for improving image quality in reduced and low dose X-ray computed tomography (CT). However, high computational cost long times so far prevented the use of SIR practical applications. Various optimization been proposed to make parallelizable execution on multicore platforms, whereas others sought improve its convergence rate. Parallelizing a set decoupled voxels within an coordinate descent (ICD) framework has...

Clustering is an important preparation step in big data processing. It may even be used to detect redundant points as well outliers. Elimination of and duplicates can serve a viable means for reduction it also aid sampling. Visual feedback very valuable here give users confidence this process. Furthermore, preprocessing seldom interactive, which stands at conflict with who seek answers immediately. The best one do incremental partial hopefully quite accurate results become available...

X-ray images obtained from synchrotron beamlines are large-scale, high-resolution and high-dynamic-range grayscale data encoding multiple complex properties of the measured materials. They typically associated with a variety metadata which increases their inherent complexity. There is wealth information embedded in these but so far scientists lack modern exploration tools to unlock hidden treasures. To bridge this gap, we propose MultiSciView, multivariate scientific x-ray image...

In computed tomography (CT), metal implants increase the inconsistencies between measured data and linear assumption of Radon transform made by analytic CT reconstruction algorithm. The appear in form dark bright bands streaks reconstructed image, collectively called artifacts. standard method for artifact reduction (MAR) replaces inconsistent with interpolated data. However, sinogram interpolation not only introduces new artifacts but it also suffers from loss detail near implanted metals....

Metal in CT-imaged objects drastically reduces the quality of these images due to severe artifacts it can cause. Most metal reduction (MAR) algorithms consider metal-affected sinogram portions as corrupted data and replace them via sophisticated interpolation methods. While schemes are successful removing artifacts, they fail recover some edge information. To address problems, frequency shift artifact algorithm (FSMAR) was recently proposed. It exploits information hidden uncorrected image...

As growing concerns on the potential side effect of radiation induced genetic, cancerous and other diseases, low-dose CT imaging is becoming a hot issue, how to minimize exposure level while maintaining diagnostic performance. In previous work, we have proposed framework that working in conjunction with image-based database. It restores image modified non-local means (NLM) expanded search window include regular-dose priors obtained from same or different patients. this paper, further develop...

The DIRECT approach for 3-D Time-of-Flight (TOF) PET reconstruction performs all iterative predictor-corrector operations directly in image space. A computational bottleneck here is the convolution with long TOF (resolution) kernels. Accelerating this operation using GPUs very important especially spatially variant resolution kernels, which cannot be efficiently implemented Fourier domain. main challenge memory cache performance at non-axis aligned directions. We devised a scheme that first...

Clustering has become an unavoidable step in big data analysis. It may be used to arrange into a compact format, making operations on manageable. However, clustering of requires not only the capability handling with large volume and high dimensionality, but also ability process streaming data, all which are less developed most current algorithms. Furthermore, processing is seldom interactive, stands at conflict users who seek answers immediately. The best one can do incrementally, such that...

In computed tomography (CT), metal implants increase the inconsistencies between measured data and linear assumption made by analytical CT reconstruction algorithm. The appear in form of dark bright bands streaks reconstructed image, collectively called artifacts. standard method for artifact reduction (MAR) replaces inconsistent with interpolated data. However, sinogram interpolation not only introduces new artifacts but it also suffers from loss detail near implanted metals. With help a...

We conducted visual analytics to find out possible reasons of the decreasing Rose-Crested Blue Pipit, a popular local bird in wildlife Preserve at Midford. Given two large scale and multidimensional datasets on chemical release meteorological information, we utilized Tableau visualization toolset reveal patterns monitor observation release. Additionally, developed prediction method connect wind direction with release, which eventually suggests origins from surrounding manufactories.

In computed tomography (CT), metal implants increase the inconsistencies between measured data and linear attenuation assumption made by analytic CT reconstruction algorithms. The give rise to dark bright bands streaks in reconstructed image, collectively called artifacts. These artifacts make it difficult for radiologists render correct diagnostic decisions. We describe a data-driven artifact reduction (MAR) algorithm image-guided spine surgery that applies scenarios which prior scan of...