Medical Image Analysis Using AM-FM Models and Methods.


Journal

IEEE reviews in biomedical engineering
ISSN: 1941-1189
Titre abrégé: IEEE Rev Biomed Eng
Pays: United States
ID NLM: 101493803

Informations de publication

Date de publication:
2021
Historique:
pubmed: 25 1 2020
medline: 27 7 2021
entrez: 25 1 2020
Statut: ppublish

Résumé

Medical image analysis methods require the use of effective representations for differentiating between lesions, diseased regions, and normal structure. Amplitude Modulation-Frequency Modulation (AM-FM) models provide effective representations through physically meaningful descriptors of complex non-stationary structures that can differentiate between the different lesions and normal structure. Based on AM-FM models, medical images are decomposed into AM-FM components where the instantaneous frequency provides a descriptor of local texture, the instantaneous amplitude captures slowly-varying brightness variations, while the instantaneous phase provides for a powerful descriptor of location, generalizing the traditionally important role of phase in the Fourier Analysis of images. Over the years, AM-FM representations have been used in a wide variety of medical image analysis applications based on a vastly reduced number of features that can be easily learned by simple classifiers. The paper provides an overview of AM-FM models and methods, followed by applications in medical image analysis. We also provide a summary of emerging trends and future directions.

Identifiants

pubmed: 31976904
doi: 10.1109/RBME.2020.2967273
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

270-289

Auteurs

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Classifications MeSH