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Related Concept Videos

Computed Tomography01:10

Computed Tomography

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Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
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DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
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Related Experiment Videos

Towards on-the-fly data post-processing for real-time tomographic imaging at TOMCAT.

Federica Marone1, Alain Studer2, Heiner Billich2

  • 1Swiss Light Source, Paul Scherrer Institute, Villigen, Switzerland.

Advanced Structural and Chemical Imaging
|March 7, 2017
PubMed
Summary

A new post-processing pipeline accelerates tomographic microscopy data analysis, enabling rapid reconstruction of 3D datasets. This tool bridges the gap between high-speed synchrotron data acquisition and computational analysis for dynamic systems research.

Keywords:
Efficient pipelineFast tomographic reconstructionHigh data ratesTomographic microscopy beamlineUltrafast X-ray tomographic imaging

Related Experiment Videos

Area of Science:

  • Advanced microscopy techniques
  • Synchrotron radiation applications
  • Computational imaging

Background:

  • Sub-second full-field tomographic microscopy is now feasible at synchrotron sources.
  • High data rates (GB/s) are expected from future diffraction-limited storage rings.
  • Current computational tools lag behind experimental advancements in efficiency.

Purpose of the Study:

  • To develop a fast and user-friendly post-processing pipeline for tomographic microscopy.
  • To address the efficiency mismatch between data acquisition and analysis.
  • To enable rapid evaluation and processing of large tomographic datasets.

Main Methods:

  • Development of a flexible post-processing software pipeline.
  • Integration with data streams directly from detectors.
  • Implementation of algorithms for rapid tomographic reconstruction.

Main Results:

  • Reconstructed tomographic datasets are delivered within seconds of data acquisition.
  • Selected tomographic slices are available in under half a second.
  • The pipeline efficiently processes terabytes of tomographic data.

Conclusions:

  • The developed pipeline overcomes the computational bottleneck in high-speed tomographic microscopy.
  • Fast data availability facilitates real-time parameter and image quality assessment.
  • Enables new possibilities for on-the-fly control of dynamic experiments.