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Computed Tomography

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.
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Related Experiment Video

Updated: Mar 25, 2026

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Published on: December 15, 2014

Breast tomosynthesis using the multiple projection algorithm adapted for stationary detectors.

A Malliori¹, K Bliznakova², Z Bliznakov¹

¹Department of Medical Physics, School of Medicine, University of Patras, Patras, Greece.

Journal of X-Ray Science and Technology

|February 19, 2016

Summary

This summary is machine-generated.

The Multiple Projection Algorithm (MPA) is validated for Breast Tomosynthesis (BT) clinical systems, offering time efficiency. Breast Tomosynthesis (BT) improves visualization of small features and dense tissue compared to 2D mammography.

Keywords:

Breast tomosynthesis image quality multiple projection algorithm reconstruction algorithms stationary detector

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Area of Science:

Medical Imaging
Radiology
Algorithm Development

Background:

Breast Tomosynthesis (BT) aims to improve breast cancer detection.
Evaluating novel reconstruction algorithms is crucial for clinical implementation.
The Multiple Projection Algorithm (MPA) has shown promise in other imaging applications.

Purpose of the Study:

To investigate the clinical validity of the Multiple Projection Algorithm (MPA) for Breast Tomosynthesis (BT).
To compare MPA performance against Back Projection (BP) using real clinical projection data.
To assess the impact of phantom thickness and pre-filtering on image quality.

Main Methods:

Utilized a CIRS-BR3D phantom (3-6 cm thickness) with 2D mammography and 25 projections (50° arc).
Adapted MPA for partial isocentric rotation with a stationary detector.
Developed a Back Projection (BP) algorithm for comparison; evaluated pre-filtering effects.

Main Results:

MPA and BP showed comparable performance in feature detection and image appearance.
MPA demonstrated faster overall processing times.
Pre-filtering improved Breast Tomosynthesis (BT) image quality, especially for thicker phantoms and superimposed structures.
Increased phantom thickness limited detection of smaller features, but filtered BT slices enhanced visualization over 2D mammograms.

Conclusions:

The Multiple Projection Algorithm (MPA) is time-efficient, compliant, and suitable for clinical Breast Tomosynthesis (BT) systems.
Breast Tomosynthesis (BT) offers superior visualization of small features and dense backgrounds compared to 2D mammography.