Clustering Methods for the Characterization of Synchrotron Radiation X‐Ray Fluorescence Images of Human Carotid Atherosclerotic Plaque

Clustering Methods for the Characterization of Synchrotron Radiation X‐Ray Fluorescence Images of Human Carotid Atherosclerotic Plaque

This study employs computational algorithms to automatically identify and classify features in X‐Ray fluorescence (XRF) microscopy images. Principal component analysis (PCA) and unsupervised machine learning algorithms, such as Gaussian mixture (GM) clustering, are implemented to label features on a...

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Bibliographic Details
Main Authors: Nathaly De La Rosa, Niccolò Peruzzi, Till Dreier, My Truong, Ulf Johansson, Sebastian Kalbfleisch, Isabel Gonçalves, Martin Bech
Format: Article
Language:English
Published: Wiley 2024-09-01
Series:Advanced Intelligent Systems
Subjects:
atherosclerosis
carotid plaque
clustering methods
unsupervised machine learning
X‐Ray fluorescence microanalysis
Online Access:https://doi.org/10.1002/aisy.202400052

Internet

https://doi.org/10.1002/aisy.202400052

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