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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.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
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Imaging Studies III: Computed Tomography01:27

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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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Recommendations for Processing Head CT Data.

John Muschelli1

  • 1Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.

Frontiers in Neuroinformatics
|September 26, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces an open-source pipeline for processing head CT scans, enabling standardized analysis from raw data to normalized brain images. This tool enhances clinical imaging research using computed tomography (CT) data.

Keywords:
CTimage analysisimage de-identificationimage normalizationimage processingneuroimagingneuroimaging analysisnon-contrast CT

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Area of Science:

  • Medical imaging analysis
  • Radiology
  • Neuroimaging

Background:

  • Magnetic resonance imaging (MRI) has established analysis pipelines.
  • Clinical diagnosis heavily relies on computed tomography (CT) scans.
  • Existing head CT processing pipelines are limited, especially for non-lesion data.

Purpose of the Study:

  • To present a comprehensive, open-source image processing pipeline for head CT data.
  • To enable standardized analysis of CT scans, applicable beyond lesion-focused research.
  • To provide a reproducible workflow from raw DICOM to spatially normalized brain images.

Main Methods:

  • Data anonymization using Clinical Trials Processor.
  • DICOM to NIfTI conversion with dcm2niix.
  • Brain extraction using BET (Brain Extraction Tool).
  • Image registration to a publicly available CT template.

Main Results:

  • A complete, documented pipeline for head CT processing is presented.
  • The pipeline successfully transforms raw DICOM data into spatially normalized brain images.
  • Code and examples are provided for reproducibility.

Conclusions:

  • The developed open-source pipeline offers a standardized approach for head CT analysis.
  • The recommended tools facilitate reproducible neuroimaging research using CT data.
  • This pipeline is applicable to most CT analyses, not just head scans.