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Related Concept Videos

Computed Tomography01:10

Computed Tomography

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...
Positron Emission Tomography01:29

Positron Emission Tomography

Positron emission tomography (PET) is a medical imaging technique involving radiopharmaceuticals — substances that emit short-lived radiation. Although the first PET scanner was introduced in 1961, it took 15 more years before radiopharmaceuticals were combined with the technique and revolutionized its potential.
One of the main requirements of a PET scan is a positron-emitting radioisotope, which is produced in a cyclotron and then attached to a substance used by the part of the body being...
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

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...
Imaging Studies II: Positron Emission Tomography and Scintigraphy01:25

Imaging Studies II: Positron Emission Tomography and Scintigraphy

Positron Emission Tomography (PET) is a medical imaging technique that provides crucial insights into the body's physiological functions at a molecular level. It is an indispensable resource for diagnosing, staging, and monitoring various illnesses, notably cancer, neurological disorders, and cardiovascular conditions.
Fundamental Principles of PET

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Related Experiment Video

Updated: May 20, 2026

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging
10:44

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

Published on: June 21, 2024

Gadgetron: an open source framework for medical image reconstruction.

Michael Schacht Hansen1, Thomas Sangild Sørensen

  • 1Division of Intramural Research, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland 20892, USA. michael.hansen@nih.gov

Magnetic Resonance in Medicine
|July 14, 2012
PubMed
Summary

The Gadgetron is a new open-source framework for medical image reconstruction. It enables flexible, reusable data processing pipelines for faster and more efficient image generation.

Related Experiment Videos

Last Updated: May 20, 2026

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging
10:44

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

Published on: June 21, 2024

Area of Science:

  • Medical Imaging
  • Computational Science
  • Software Engineering

Background:

  • Medical image reconstruction is computationally intensive.
  • Existing frameworks lack flexibility and modularity.
  • Need for efficient, shareable reconstruction tools.

Purpose of the Study:

  • Introduce the Gadgetron, an open-source framework for medical image reconstruction.
  • Provide a flexible, streaming data processing pipeline architecture.
  • Facilitate module reuse and the addition of new reconstruction functionalities.

Main Methods:

  • Developed a streaming data processing pipeline architecture using configurable modules ('Gadgets').
  • Implemented dynamic run-time configuration via extensible markup language.
  • Enabled C/C++ and Python (via wrappers) for Gadget development.
  • Integrated generic toolboxes for data-parallel (GPU) execution.

Main Results:

  • The Gadgetron framework supports modularity and code reuse.
  • New reconstruction modules can be added via a plugin-like architecture.
  • Demonstrated application to Cartesian and non-Cartesian parallel magnetic resonance imaging.

Conclusions:

  • The Gadgetron offers a flexible and extensible platform for medical image reconstruction.
  • Its modular design promotes efficient development and sharing of reconstruction algorithms.
  • The framework is applicable across various medical imaging modalities, with a focus on MRI.