Independent Component Analysis for Noise and Artifact Removal in Three-Dimensional Polarized Light Imaging

Kai Benning*, Miriam Menzel, Jan André Reuter, Markus Axer

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

1 Citation (Scopus)

Abstract

In recent years, Independent Component Analysis (ICA) has successfully been applied to remove noise and artifacts in images obtained from Three-dimensional Polarized Light Imaging (3D-PLI) at the mesoscale (i.e., 64 μ m). Here, we present an automatic denoising procedure for gray matter regions that allows to apply the ICA also to microscopic images, with reasonable computational effort. Apart from an automatic segmentation of gray matter regions, we applied the denoising procedure to several 3D-PLI images from a rat and a vervet monkey brain section.

Original languageEnglish
Title of host publicationBrain-Inspired Computing - 4th International Workshop, BrainComp 2019, Revised Selected Papers
EditorsKatrin Amunts, Lucio Grandinetti, Thomas Lippert, Nicolai Petkov
PublisherSpringer
Pages90-102
ISBN (Print)9783030824266
DOIs
Publication statusPublished - 2021
Externally publishedYes
Event4th International Workshop on Brain-Inspired Computing, BrainComp 2019 - Cetraro, Italy
Duration: 15 Jul 201919 Jul 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12339 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Workshop on Brain-Inspired Computing, BrainComp 2019
Country/TerritoryItaly
CityCetraro
Period15/07/1919/07/19

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