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[This article belongs to Volume - 70, Issue - 11]
Published on : 2025-11-01 21:18:20
Article Code: AMJ-01-11-2025-12356
Title : The Fourier Transform: A Mathematical Imperative for Advanced Disease Detection in Medical Imaging
Author(s) : Nabil K. Salman
Abstract :
Background The Fourier Transform (FT) is a mathematical technique central to modern medical imaging, enabling
frequency-based analysis of acquired signals. It is used extensively in image reconstruction, enhancement, and
diagnostic feature extraction.
Objective To analyze the central role of the Fourier Transform in clinical imaging pipelines with emphasis on
reconstruction, noise suppression, and disease detection accuracy.
Methods A literature-based analysis was conducted focusing on frequency separation, spectral filtering, artifact
suppression, and integration within deep learning architectures.
Results FT-based processing improves diagnostic clarity by separating structural information from high-frequency
noise, enhancing organ boundaries, and improving lesion visibility. Furthermore, FT integration into deep learning
improves robustness against noisy or adversarial inputs.
Conclusion The Fourier Transform remains a cornerstone for reliable medical imaging, providing essential
contributions to reconstruction quality, computer-aided diagnosis (CAD), radiomics, and advanced disease detection
workflows.