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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 X-rays, and by 1900, X-ray was widely...

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Related Experiment Video

Updated: Jul 7, 2026

X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging

X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging

Published on: September 11, 2011

Automatic anatomically selective image enhancement in digital chest radiography.

M I Sezn¹, A M Teklap, R Schaetzing

¹Eastman Kodak Co., Rochester, NY.

IEEE Transactions on Medical Imaging

|January 1, 1989

Summary

This study introduces an automated method for enhancing digital chest radiographs by distinguishing between lung fields and the mediastinum. The technique improves image quality by applying tailored enhancements to different anatomical regions.

Related Experiment Videos

Last Updated: Jul 7, 2026

X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging

X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging

Published on: September 11, 2011

Area of Science:

Medical Imaging
Radiography
Image Processing

Background:

Digital chest radiographs require varied enhancement for optimal visualization of different anatomical structures.
Simultaneously optimizing enhancement for both lung fields and mediastinum presents a challenge in medical imaging.

Purpose of the Study:

To develop an automated technique for anatomically selective enhancement of digital chest radiographs.
To address the differing enhancement needs of the lung field and mediastinum within a single image.

Main Methods:

Utilized a peak detection algorithm and rule-based system on image histograms to automatically identify a gray-level threshold.
Applied anatomically selective gray-scale modification and unsharp masking based on the determined threshold.
Incorporated local contrast adaptation with an asymmetric emphasis parameter to mitigate artifacts from unsharp masking.

Main Results:

Successfully developed an automated method for anatomically selective enhancement of chest radiographs.
The technique effectively differentiates and applies distinct enhancements to lung fields and mediastinum.
Artifact suppression was achieved through adaptive contrast modification during unsharp masking.

Conclusions:

The proposed technique offers an automated and effective approach to enhance digital chest radiographs.
Anatomically selective enhancement improves the visualization of critical structures in chest imaging.
The method shows promise in reducing common artifacts associated with image enhancement techniques.