protocol
Segmentation and quantification of subcellular structures in fluorescence microscopy images using Squassh Aurélien Rizk1,2, Grégory Paul2,5, Pietro Incardona2, Milica Bugarski1, Maysam Mansouri1, Axel Niemann3, Urs Ziegler4, Philipp Berger1 & Ivo F Sbalzarini2 1Paul Scherrer Institute, Biomolecular Research, Molecular Cell Biology, Villigen PSI, Switzerland. 2MOSAIC Group, Center of
Systems Biology Dresden, Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany. 3ETH Zurich, Institute of Molecular Health Sciences, Zürich, Switzerland. 4Center for Microscopy and Image Analysis, University of Zurich, Zürich, Switzerland. 5Present address: ETH Zurich, Computer Vision Laboratory, Zürich, Switzerland. Correspondence should be addressed to P.B. ([email protected]) or I.F.S. ([email protected]).
© 2014 Nature America, Inc. All rights reserved.
Published online 13 February 2014; doi:10.1038/nprot.2014.037
Detection and quantification of fluorescently labeled molecules in subcellular compartments is a key step in the analysis of many cell biological processes. Pixel-wise colocalization analyses, however, are not always suitable, because they do not provide object-specific information, and they are vulnerable to noise and background fluorescence. Here we present a versatile protocol for a method named ‘Squassh’ (segmentation and quantification of subcellular shapes), which is used for detecting, delineating and quantifying subcellular structures in fluorescence microscopy images. The workflow is implemented in freely available, user-friendly software. It works on both 2D and 3D images, accounts for the microscope optics and for uneven image background, computes cell masks and provides subpixel accuracy. The Squassh software enables both colocalization and shape analyses. The protocol can be applied in batch, on desktop computers or computer clusters, and it usually requires
Segmentation and quantification of subcellular structures in fluorescence microscopy images using Squassh Aurélien Rizk1,2, Grégory Paul2,5, Pietro Incardona2, Milica Bugarski1, Maysam Mansouri1, Axel Niemann3, Urs Ziegler4, Philipp Berger1 & Ivo F Sbalzarini2 1Paul Scherrer Institute, Biomolecular Research, Molecular Cell Biology, Villigen PSI, Switzerland. 2MOSAIC Group, Center of
Systems Biology Dresden, Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany. 3ETH Zurich, Institute of Molecular Health Sciences, Zürich, Switzerland. 4Center for Microscopy and Image Analysis, University of Zurich, Zürich, Switzerland. 5Present address: ETH Zurich, Computer Vision Laboratory, Zürich, Switzerland. Correspondence should be addressed to P.B. ([email protected]) or I.F.S. ([email protected]).
© 2014 Nature America, Inc. All rights reserved.
Published online 13 February 2014; doi:10.1038/nprot.2014.037
Detection and quantification of fluorescently labeled molecules in subcellular compartments is a key step in the analysis of many cell biological processes. Pixel-wise colocalization analyses, however, are not always suitable, because they do not provide object-specific information, and they are vulnerable to noise and background fluorescence. Here we present a versatile protocol for a method named ‘Squassh’ (segmentation and quantification of subcellular shapes), which is used for detecting, delineating and quantifying subcellular structures in fluorescence microscopy images. The workflow is implemented in freely available, user-friendly software. It works on both 2D and 3D images, accounts for the microscope optics and for uneven image background, computes cell masks and provides subpixel accuracy. The Squassh software enables both colocalization and shape analyses. The protocol can be applied in batch, on desktop computers or computer clusters, and it usually requires
