Segmentation of cell structures using Model-Based Set Covering with iterative reweighting

We present a new method for cell segmentation which combines a marked point process model with a combinatorics-based method of finding global optima. The method employs an energy term that assesses possible segmentations by their fidelity to both local image information and a simple model of cell in...

Full description

Saved in:
Bibliographic Details
Main Authors: Markowsky, Peter, Reith, Svenja, Zuber, Tabea E., Konig, Rainer, Rohr, Karl, Schnorr, Christoph
Format: Conference Proceeding
Language:English
Subjects:
Approximation algorithms
Cell Segmentation
Computational modeling
Convergence
Image segmentation
Iterative Candidate Reweighting
Marked Point Process
Microscopy
Minimization
Randomized Set Covering
Shape
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We present a new method for cell segmentation which combines a marked point process model with a combinatorics-based method of finding global optima. The method employs an energy term that assesses possible segmentations by their fidelity to both local image information and a simple model of cell interaction, and we use a randomized iterative reweighting technique for its minimization. Our approach was successfully applied to cell microscopy images of varying difficulty and experimentally compared with both a standard segmentation method as well as a method based on Multiple Birth and Cut [1]. The proposed method is found to improve upon previous approaches.
ISSN:1945-8452
DOI:10.1109/ISBI.2017.7950545