By Topic

3D Geometry-Based Quantification of Colocalizations in Multichannel 3D Microscopy Images of Human Soft Tissue Tumors

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

9 Author(s)
Worz, S.. ; Dept. Bioinf. & Functional Genomics, Univ. of Heidelberg, Heidelberg, Germany ; Sander, P. ; Pfannmoller, M. ; Rieker, R.J.
more authors

We introduce a new model-based approach for automatic quantification of colocalizations in multichannel 3D microscopy images. The approach uses different 3D parametric intensity models in conjunction with a model fitting scheme to localize and quantify subcellular structures with high accuracy. The central idea is to determine colocalizations between different channels based on the estimated geometry of the subcellular structures as well as to differentiate between different types of colocalizations. A statistical analysis was performed to assess the significance of the determined colocalizations. This approach was used to successfully analyze about 500 three-channel 3D microscopy images of human soft tissue tumors and controls.

Published in:

Medical Imaging, IEEE Transactions on  (Volume:29 ,  Issue: 8 )