Title
Fast segmentation from blurred data in 3D fluorescence microscopy.
Abstract
We develop a fast algorithm for segmenting 3D images from linear measurements based on the Potts model (or piecewise constant Mumford-Shah model). To that end, we first derive suitable space discretizations of the 3D Potts model, which are capable of dealing with 3D images defined on non-cubic grids. Our discretization allows us to utilize a specific splitting approach, which results in decoupled ...
Year
DOI
Venue
2017
10.1109/TIP.2017.2716843
IEEE Transactions on Image Processing
Keywords
Field
DocType
Three-dimensional displays,Image segmentation,Microscopy,Graphics processing units,Image reconstruction,Solid modeling
Graphics,Computer vision,Discretization,Segmentation,Deconvolution,Image segmentation,Solid modeling,Artificial intelligence,Piecewise,Potts model,Mathematics
Journal
Volume
Issue
ISSN
26
10
1057-7149
Citations 
PageRank 
References 
1
0.37
32
Authors
4
Name
Order
Citations
PageRank
Martin Storath113812.69
Dennis Rickert251.16
Michael Unser3285.24
andreas weinmann413812.81