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» Learning to segment dense cell nuclei with shape prior
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CVPR
2012
IEEE
10 years 4 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,...
ICPR
2008
IEEE
12 years 8 months ago
Segmentation of overlapping/aggregating nuclei cells in biological images
This paper presents a method of overlapping/aggregating nuclei cells segmentation. This method is based on the watershed segmentation algorithm, but the specificity of this work i...
Florence Cloppet, Arnaud Boucher
DAGM
2010
Springer
12 years 2 months ago
Computational TMA Analysis and Cell Nucleus Classification of Renal Cell Carcinoma
Abstract. We consider an automated processing pipeline for tissue micro array analysis (TMA) of renal cell carcinoma. It consists of several consecutive tasks, which can be mapped ...
Peter J. Schüffler, Thomas J. Fuchs, Cheng So...
MICCAI
2007
Springer
13 years 2 months ago
Active-Contour-Based Image Segmentation Using Machine Learning Techniques
Abstract. We introduce a non-linear shape prior for the deformable model framework that we learn from a set of shape samples using recent manifold learning techniques. We model a c...
Patrick Etyngier, Florent Ségonne, Renaud K...
BMCBI
2010
218views more  BMCBI 2010»
11 years 11 months ago
A hybrid blob-slice model for accurate and efficient detection of fluorescence labeled nuclei in 3D
Background: To exploit the flood of data from advances in high throughput imaging of optically sectioned nuclei, image analysis methods need to correctly detect thousands of nucle...
Anthony Santella, Zhuo Du, Sonja Nowotschin, Anna-...
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