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A variational approach to vesicle membrane reconstruction from fluorescence imaging

  • Biological applications like vesicle membrane analysis involve the precise segmentation of 3D structures in noisy volumetric data, obtained by techniques like magnetic resonance imaging (MRI) or laser scanning microscopy (LSM). Dealing with such data is a challenging task and requires robust and accurate segmentation methods. In this article, we propose a novel energy model for 3D segmentation fusing various cues like regional intensity subdivision, edge alignment and orientation information. The uniqueness of the approach consists in the definition of a new anisotropic regularizer, which accounts for the unbalanced slicing of the measured volume data, and the generalization of an efficient numerical scheme for solving the arising minimization problem, based on linearization and fixed-point iteration. We show how the proposed energy model can be optimized globally by making use of recent continuous convex relaxation techniques. The accuracy and robustness of the presented approach are demonstrated by evaluating it on multiple real data sets and comparing it to alternative segmentation methods based on level sets. Although the proposed model is designed with focus on the particular application at hand, it is general enough to be applied to a variety of different segmentation tasks.

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Metadaten
Author:Kalin Kolev, Norbert Kirchgeßner, Sebastian Houben, Agnes Csiszár, Wolfgang Rubner, Christoph PalmORCiDGND, Björn Eiben, Rudolf Merkel, Daniel Cremers
DOI:https://doi.org/10.1016/j.patcog.2011.04.019
Parent Title (English):Pattern Recognition
Publisher:Elsevier
Document Type:Article
Language:English
Year of first Publication:2011
Release Date:2019/12/20
Tag:3D segmentation; Convex optimization; Fluorescence imaging; Vesicle membrane analysis
GND Keyword:Dreidimensionale Bildverarbeitung; Bildsegmentierung; Konvexe Optimierung
Volume:44
Issue:12
First Page:2944
Last Page:2958
Institutes:Fakultät Informatik und Mathematik
Fakultät Informatik und Mathematik / Regensburg Medical Image Computing (ReMIC)
Begutachtungsstatus:peer-reviewed
research focus:Lebenswissenschaften und Ethik