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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

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Published on: August 30, 2013

An automatic correction method for the heel effect in digitized mammography images.

Marcelo Zanchetta do Nascimento¹, Annie France Frère, Fernao Germano

¹Centro de Matemática, Computação e Cognição, Universidade Federal do ABC, Rua Santa Adélia, Santo André, SP, Brazil. marcelo.nascimento@ufabc.edu.br

Journal of Digital Imaging

|September 12, 2007

Summary

This study introduces a novel method to correct the Heel effect in mammograms, improving accuracy for computer-aided cancer detection. The technique effectively reduces radiation nonuniformity, enhancing diagnostic image quality.

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Area of Science:

Medical Imaging
Radiological Physics
Digital Image Processing

Background:

The Heel effect causes radiation field nonuniformity in mammography.
This significantly impacts computer-aided diagnosis (CAD) for early cancer detection.
Accurate mammograms are crucial for reliable cancer screening.

Purpose of the Study:

To present a method for correcting the Heel effect in mammography images.
To improve the accuracy of computer-aided diagnosis by addressing radiation nonuniformity.
To enable more reliable early cancer detection through enhanced image quality.

Main Methods:

A simulation method calculates radiation intensities across the image plane.
The method analyzes optical density in digitized mammograms.
It utilizes the Gaussian and logarithmic distributions characteristic of the Heel effect to identify the radiation field center and cathode-anode axis.

Main Results:

The proposed method accurately determines the radiation field center and cathode-anode axis.
Measurements show an average deviation of 2.49 mm (perpendicular) and 2.02 mm (parallel) to the axis compared to commercial equipment.
The technique effectively eliminates approximately 94% of the Heel effect, allowing objects to accurately reflect X-ray absorption.

Conclusions:

The developed method successfully corrects for the Heel effect in mammography.
This correction enhances the reliability of mammograms for computer-aided diagnosis and cancer detection.
The technique shows potential for application with clinical and digital mammography images.