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Enhancing CT 3D Images by Independent Component Analysis of Projection Images

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review


Original languageEnglish
Title of host publication15th Mediterranean Conference on Medical and Biological Engineering and Computing – MEDICON 2019 - Proceedings of MEDICON 2019
EditorsJorge Henriques, Paulo de Carvalho, Nuno Neves
Number of pages9
ISBN (Print)9783030316341
Publication statusPublished - 2020
Publication typeA4 Article in a conference publication
EventMediterranean Conference on Medical and Biological Engineering and Computing - Coimbra, Portugal
Duration: 26 Sep 201928 Sep 2019

Publication series

NameIFMBE Proceedings
ISSN (Print)1680-0737
ISSN (Electronic)1433-9277


ConferenceMediterranean Conference on Medical and Biological Engineering and Computing


Computed tomography (CT) is an imaging modality producing 3D images from sets of 2D X-ray images taken around the object. The images are noisy by nature, and segmentation of the 3D images is tedious. Also, detection of low contrast objects may be difficult, if not impossible. Here, we propose an independent component analysis (ICA) based method to process sets of 2D projection images prior to 3D reconstruction to remove noise, and to enhance objects for detection and segmentation. In this paper, a proof-of-concept is provided: the proposed method was able to separate noise and image components, as well as to make visible objects that were not observable in 3D images without processing. We demonstrate our method in object separation with 2D slice image processing simulations, and by enhancing a 3D image of a polymer sample taken with Xradia MicroXCT-400. The method is applicable in any CT tomography for which a number of project image sets with different contrasts can be taken, e.g., in multispectral fashion.

ASJC Scopus subject areas


  • 3D imaging, Computed tomography, CT, Image processing, Independent component analysis, Micro-CT, µCT

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