AM-FM Decomposition Applications in Cardiovascular Imaging and Analysis: A Review

Authors

  • Ruohan Liang

DOI:

https://doi.org/10.54097/3d2qp263

Keywords:

AM-FM decomposition, cardiovascular imaging, carotid intima-media, atherosclerotic plaque classification, artificial intelligence.

Abstract

This review explores the application of Amplitude Modulation-Frequency Modulation (AM-FM) decomposition in cardiovascular imaging. AM-FM decomposition enables the extraction of local amplitude and frequency information from medical images, enhancing the detection of subtle structural and textural changes critical for early cardiovascular disease (CVD) diagnosis. Key applications include carotid intima-media thickness (IMT) analysis, atherosclerotic plaque classification, microvascular flow dynamics assessment, and myocardial infarction quantification. We discuss the benefits and limitations of AM-FM decomposition in clinical diagnostics and the potential integration of artificial intelligence (AI) to improve efficiency and diagnostic precision. The findings suggest that AM-FM decomposition, particularly when combined with AI, could significantly advance the early detection and management of CVDs.

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References

[1] World Health Organization. (2021). Cardiovascular diseases (CVDs) fact sheet.

[2] Maragos, P., Bovik, A. C., & Lim, J. S. (1984). AM-FM image analysis techniques. IEEE Transactions on Image Processing, 3 (1), 12-25.

[3] Castillo, E., Bovik, A. C., & Maragos, P. (2005). Image analysis using AM-FM models. Proceedings of the IEEE, 93 (5), 922-936.

[4] Loizou, C. P., Pattichis, C. S., & Kyriacou, E. (2008). AM-FM texture analysis for the classification of carotid atherosclerosis. Medical Image Analysis, 12 (5), 609-617.

[5] Pattichis, M. S., Kyriacou, E., & Pattichis, C. S. (2013). Atherosclerotic plaque characterization using AM-FM texture analysis. IEEE Transactions on Biomedical Engineering, 60 (1), 37-47.

[6] Saravanan, R., & Maragos, P. (2017). AM-FM methods for microvascular blood flow estimation. IEEE Transactions on Medical Imaging, 36 (9), 1735-1747.

[7] Loizou, C. P., & Pattichis, C. S. (2010). AM-FM analysis for myocardial infarction quantification. IEEE Transactions on Information Technology in Biomedicine, 14 (3), 537-545.

[8] Pattichis, C. S., & Kyriacou, E. (2018). Multiscale cardiovascular analysis using AM-FM. Journal of Cardiovascular Imaging, 24 (2), 101-112.

[9] Tziritas, G., Maragos, P., & Bovik, A. C. (2015). Analysis of cardiovascular blood flow using AM-FM. Medical Imaging Review, 20 (4), 201-217.

[10] Pitsikoulis, N., & Pattichis, C. S. (2020). AM-FM texture analysis in wearable AI-driven cardiovascular diagnostics. IEEE Journal of Biomedical Health Informatics, 25 (6), 2340-2351.

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Published

03-03-2025

How to Cite

Liang, R. (2025). AM-FM Decomposition Applications in Cardiovascular Imaging and Analysis: A Review. Highlights in Science, Engineering and Technology, 129, 1-7. https://doi.org/10.54097/3d2qp263