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Related Concept Videos

X-ray Imaging01:24

X-ray Imaging

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German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with...
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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.
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Different notations are used to represent the three-dimensional structure of molecules on two-dimensional surfaces. One of the most commonly used representations is the dash-wedge formula. The dashed wedges, solid wedges, and the plane lines indicate the groups situated behind the plane, coming out of the plane, and in the plane, respectively.
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Transmission electron microscopy (TEM) can be used to determine the 3D structure of biological samples with the help of techniques such as electron microscope tomography and single-particle reconstruction. While single-particle reconstruction can examine macromolecules and macromolecular complexes in vitro conditions only, tomography permits the study of cell components or small cells in vivo.
Electron Tomography
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Positron Emission Tomography01:29

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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.
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Fischer Projections02:18

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Learning to draw Fischer projections of molecules and understanding their relevance plays a crucial role in the visual depiction of organic molecules. A Fischer projection is a two-dimensional projection on a planar surface to simplify the three-dimensional wedge–dash representation of molecules. This is especially helpful in the case of molecules with multiple chiral centers that can be difficult to draw. Here, all the bonds of interest are represented as horizontal or vertical lines.
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Related Experiment Video

Updated: Oct 4, 2025

Non-invasive 3D-Visualization with Sub-micron Resolution Using Synchrotron-X-ray-tomography
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Novel-view X-ray projection synthesis through geometry-integrated deep learning.

Liyue Shen1, Lequan Yu2, Wei Zhao2

  • 1Department of Electrical Engineering, Stanford University, Stanford, CA, USA.

Medical Image Analysis
|February 8, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a Deep Learning-based Geometry-Integrated Projection Synthesis (DL-GIPS) framework to generate new X-ray projection views from existing ones. This method reduces radiation dose and simplifies workflow for stereoscopic and volumetric imaging.

Keywords:
Geometry-integrated deep learningProjection view synthesisX-ray imaging

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Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Radiology

Background:

  • X-ray imaging is crucial for clinical diagnosis and interventions.
  • Multiple X-ray views enhance anatomical information for stereoscopic and volumetric imaging.
  • Acquiring multiple projections increases radiation exposure and complicates clinical procedures.

Purpose of the Study:

  • To develop a method for synthesizing novel-view X-ray projections from existing ones.
  • To reduce the need for additional X-ray data acquisition.
  • To alleviate radiation dose and streamline clinical workflows.

Main Methods:

  • A Deep Learning-based Geometry-Integrated Projection Synthesis (DL-GIPS) framework was proposed.
  • The DL-GIPS model extracts geometry and texture features from source-view projections.
  • Geometry transformation and image generation synthesize target-view projections.

Main Results:

  • The DL-GIPS model successfully generated novel-view X-ray projections.
  • Feasibility was demonstrated using lung imaging cases.
  • The approach shows potential for generalized multi-projection synthesis.

Conclusions:

  • The DL-GIPS framework offers a viable strategy for synthesizing X-ray projections.
  • This method can significantly reduce data acquisition efforts in stereoscopic and volumetric imaging.
  • It presents a new paradigm for efficient medical imaging acquisition.