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Medical Image Analysis Using AM-FM Models and Methods.

Kyriacos P Constantinou, Ioannis P Constantinou, Constantinos S Pattichis

IEEE Reviews in Biomedical Engineering

|January 25, 2020

Summary

This summary is machine-generated.

Amplitude Modulation-Frequency Modulation (AM-FM) models offer effective medical image representations for distinguishing lesions and normal structures. These models provide physically meaningful descriptors, simplifying analysis and enabling accurate classification in various medical imaging applications.

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Area of Science:

Medical Image Analysis
Signal Processing
Biomedical Engineering

Background:

Effective representations are crucial for medical image analysis to differentiate between lesions, diseased regions, and normal structures.
Traditional methods may struggle with complex, non-stationary structures common in medical imaging.

Purpose of the Study:

To provide an overview of Amplitude Modulation-Frequency Modulation (AM-FM) models and their applications in medical image analysis.
To highlight the utility of AM-FM representations for differentiating various tissue types and abnormalities.

Main Methods:

Decomposition of medical images into AM-FM components.
Utilizing instantaneous frequency for local texture description.
Employing instantaneous amplitude for brightness variations and instantaneous phase for location description.

Main Results:

AM-FM models provide physically meaningful descriptors for complex non-stationary structures.
These representations effectively differentiate between lesions and normal structures.
AM-FM features enable simple classifiers to learn from a reduced set of parameters.

Conclusions:

AM-FM models offer a powerful and efficient approach for medical image analysis.
Their physically meaningful descriptors facilitate accurate differentiation of pathologies.
Emerging trends suggest continued advancements and broader applications in the future.