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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...
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...

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A Gaussian fitting-based analysis method for multiple image radiography with integrated angular calibration, MIR2.

Farangis Foroughi1,2, Gurpreet Kaur Aulakh3, David Krapohl2

  • 1Department of Physics and Engineering Physics, College of Arts and Science, University of Saskatchewan, 116 Science Place, Saskatoon, Saskatchewan S7N 5E2, Canada.

Physics in Medicine and Biology
|November 21, 2025
PubMed
Summary
This summary is machine-generated.

A new Multiple Image Radiography (MIR) analysis framework, MIR2, improves soft-tissue imaging by eliminating normalization and alignment steps. This robust method reduces artifacts and simplifies workflows for biomedical and material imaging.

Keywords:
dose-limited imagingmultiple image radiographyphase-based x-ray imagingsoft tissue imaging

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Area of Science:

  • Medical Imaging
  • X-ray Phase-Contrast Imaging
  • Biophysics

Background:

  • Multiple Image Radiography (MIR) enhances soft-tissue visibility using X-ray phase-contrast.
  • Conventional MIR requires normalization and precise alignment, leading to artifacts and sensitivity to drift.
  • Ultra-small-angle X-ray scattering (USAXS) signals are captured alongside absorption and refraction.

Purpose of the Study:

  • To develop an improved analysis framework (MIR2) for Multiple Image Radiography.
  • To eliminate the need for normalization and angular alignment in MIR data processing.
  • To enhance image stability and reduce artifacts in X-ray phase-contrast imaging.

Main Methods:

  • Developed MIR2, an analysis framework independent of object/reference normalization and angular alignment.
  • Applied angular calibration using the dynamical theory of diffraction.
  • Utilized pixel-wise Gaussian fitting of angular intensity profiles, similar to MIR, but with intrinsic artifact suppression.

Main Results:

  • MIR2 produced more stable and artifact-reduced images compared to conventional MIR.
  • Validation performed on test objects (PMMA, paper) and *in vivo* mouse lung imaging.
  • Demonstrated intrinsic artifact suppression without additional correction algorithms.

Conclusions:

  • MIR2 offers a simpler, less error-prone, and more robust MIR analysis pipeline.
  • The method streamlines workflows for biomedical and material imaging applications.
  • MIR2 is suitable for dose-limited imaging scenarios, improving image quality and stability.