Active Appearance Segmentation for Intensity Inhomogeneity in Light Sheet Fluorescence Microscopy

Casper Bo Jensen, Mark Lyksborg, J. Hecksher-Sørensen, A. Secher, Knut Conradsen, Anders Bjorholm Dahl

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Active Appearance Models (AAM) are used for annotating or segmenting shapes in biomedical images. Performance relies heavily on the image data used to train the AAM. In this paper we improve the generalization properties of the model by making it robust to slowly varying spatial intensity inhomogeneities which are often seen in Light Sheet Fluorescence Microscopy (LSFM) images. This robustness is achieved by modelling the appearance of an image as a regularized Normalized Gradient Field (rNGF). We perform two experiments to challenge the model. First it is tested using a repeated leave-one-out approach on images with minimal imperfections where the left out images are corrupted by a simulated bias field and segmented using the AAM. Secondly we test the model on LSFM images with common acquisition problems. In both experiments the proposed approach outperforms the often used AAM implementation based on Sum of Squared Differences.
Original languageEnglish
Title of host publicationProceedings of the IEEE 13th International Symposium on Biomedical Imaging (ISBI 2016)
PublisherIEEE
Publication date2016
Pages217-220
DOIs
Publication statusPublished - 2016
Event13th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Clarion Congress Hotel, Prague, Czech Republic
Duration: 13 Apr 201616 Apr 2016
Conference number: 13
http://biomedicalimaging.org/2016/
https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html%3FConf_ID%3D31200

Conference

Conference13th IEEE International Symposium on Biomedical Imaging
Number13
LocationClarion Congress Hotel
CountryCzech Republic
CityPrague
Period13/04/201616/04/2016
Internet address

Keywords

  • Active Appearance Model
  • Regularized Normalized Gradient Field
  • Light Sheet Fluorescence Microscopy
  • Segmentation

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