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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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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 Video

Updated: Aug 14, 2025

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
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Clinical prototype implementation enabling an improved day-to-day mammography compression.

Madeleine Hertel1, Chang Liu2, Haobo Song3

  • 1Siemens Healthcare GmbH, 91301 Forchheim, Germany; Institute for Medical Engineering and Research Campus STIMULATE, Otto-von-Guericke-University, 39106 Magdeburg, Germany.

Physica Medica : PM : an International Journal Devoted to the Applications of Physics to Medicine and Biology : Official Journal of the Italian Association of Biomedical Physics (AIFB)
|January 15, 2023
PubMed
Summary

This study introduces a new prototype for mammography that measures breast compression pressure in real-time. This innovation aims to standardize compression, reducing patient discomfort by ensuring uniform pressure across all breast sizes.

Keywords:
Breast imagingCompressionDeep-learningMammography

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Area of Science:

  • Medical Imaging
  • Biomedical Engineering
  • Radiology

Background:

  • Mammography utilizes breast compression for image quality, but current methods lack standardized guidelines for execution.
  • Existing mammography units rely on compression force and breast thickness, leading to variable pressure and discomfort, especially for smaller breast sizes.

Purpose of the Study:

  • To develop a more uniform breast compression method in mammography by utilizing pressure as the key parameter.
  • To address the issue of inconsistent compression levels and associated patient discomfort in mammography procedures.

Main Methods:

  • A prototype system was developed to measure breast compression pressure in real-time without direct patient contact.
  • A deep learning model was employed to automatically segment the breast-compression paddle contact area using an optical camera.

Main Results:

  • The deep learning model achieved high accuracy in contact area segmentation, with a mean pixel accuracy of 96.7% and a Dice score of 93.6%.
  • The pressure display updates rapidly (over five times per second), making it suitable for clinical integration.

Conclusions:

  • The developed prototype offers a promising solution for guiding improved breast compression routines in mammography.
  • Real-time pressure-based measurement can lead to more consistent and comfortable mammography procedures.