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» Graph Cuts and Efficient N-D Image Segmentation
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CVPR
2012
IEEE
11 years 11 months ago
Learning to segment dense cell nuclei with shape prior
We study the problem of segmenting multiple cell nuclei from GFP or Hoechst stained microscope images with a shape prior. This problem is encountered ubiquitously in cell biology ...
Xinghua Lou, Ullrich Köthe, Jochen Wittbrodt,...
PAMI
2010
188views more  PAMI 2010»
13 years 3 months ago
Watershed Cuts: Thinnings, Shortest Path Forests, and Topological Watersheds
We recently introduced the watershed cuts, a notion of watershed in edge-weighted graphs. In this paper, our main contribution is a thinning paradigm from which we derive three alg...
Jean Cousty, Gilles Bertrand, Laurent Najman, Mich...
ICIP
2010
IEEE
13 years 6 months ago
Robust segmentation of lung tissue in chest CT scanning
This paper deals with segmentation of the lung tissues from low dose CT (LDCT) scans of the chest. Goal is correct segmentation as well as maintaining the details of the lung regi...
Amal A. Farag, James Graham, Aly Farag
CVPR
2000
IEEE
14 years 1 months ago
Perceptual Grouping and Segmentation by Stochastic Clustering
We use cluster analysis as a unifying principle for problems from low, middle and high level vision. The clustering problem is viewed as graph partitioning, where nodes represent ...
Yoram Gdalyahu, Noam Shental, Daphna Weinshall
PR
2007
189views more  PR 2007»
13 years 8 months ago
Information cut for clustering using a gradient descent approach
We introduce a new graph cut for clustering which we call the Information Cut. It is derived using Parzen windowing to estimate an information theoretic distance measure between p...
Robert Jenssen, Deniz Erdogmus, Kenneth E. Hild II...