Smooth 2D manifold extraction from 3D image stack

Three-dimensional fluorescence microscopy followed by image processing is routinely used to study biological objects at various scales such as cells and tissue. However, maximum intensity projection, the most broadly used rendering tool, extracts a discontinuous layer of voxels, obliviously creating important artifacts and possibly misleading interpretation. Here we propose smooth manifold extraction, an algorithm that produces a continuous focused 2D extraction from a 3D volume, hence preserving local spatial relationships. We demonstrate the usefulness of our approach by applying it to various biological applications using confocal and wide-field microscopy 3D image stacks. We provide a parameter-free ImageJ/Fiji plugin that allows 2D visualization and interpretation of 3D image stacks with maximum accuracy.

[1]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[2]  Shree K. Nayar,et al.  Shape from Focus , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  W. Cathey,et al.  Extended depth of field through wave-front coding. , 1995, Applied optics.

[4]  Jeffrey L Clendenon,et al.  Voxx: a PC-based, near real-time volume rendering system for biological microscopy. , 2002, American journal of physiology. Cell physiology.

[5]  Gemma Piella,et al.  A general framework for multiresolution image fusion: from pixels to regions , 2003, Inf. Fusion.

[6]  Erik Brauner,et al.  Informatics and Quantitative Analysis in Biological Imaging , 2003, Science.

[7]  Joseph G. Gleeson,et al.  Transgenic Mouse Line with Green-fluorescent Protein-labeled Centrin 2 allows Visualization of the Centrosome in Living Cells , 2004, Transgenic Research.

[8]  Michael Unser,et al.  Complex wavelets for extended depth‐of‐field: A new method for the fusion of multichannel microscopy images , 2004, Microscopy research and technique.

[9]  J. Sibarita.  Deconvolution microscopy. , 2005, Advances in biochemical engineering/biotechnology.

[10]  Jamie P. Heather,et al.  A review of image fusion technology in 2005 , 2005, SPIE Defense + Commercial Sensing.

[11]  S. Shorte,et al.  Quantitative four-dimensional tracking of cytoplasmic and nuclear HIV-1 complexes , 2006, Nature Methods.

[12]  Zhongliang Jing,et al.  Evaluation of focus measures in multi-focus image fusion , 2007, Pattern Recognit. Lett..

[13]  Tae-Sun Choi,et al.  Consideration of illumination effects and optimization of window size for accurate calculation of depth map for 3D shape recovery , 2007, Pattern Recognit..

[14]  Dimitri Van De Ville,et al.  Model-Based 2.5-D Deconvolution for Extended Depth of Field in Brightfield Microscopy , 2008, IEEE Transactions on Image Processing.

[15]  A. Ardeshir Goshtasby,et al.  An adaptive window mechanism for image smoothing , 2008, Comput. Vis. Image Underst..

[16]  Tae-Sun Choi,et al.  Analysis of Effects of Texture Reflectance and Source Illumination on Focus Measures for Microscopic Images , 2009, 2009 Second International Conference on Computer and Electrical Engineering.

[17]  Tae-Sun Choi,et al.  Accurate shape from focus based on focus adjustment in optical microscopy , 2009, Microscopy research and technique.

[18]  Tae-Sun Choi,et al.  A novel method for shape from focus in microscopy using Bezier surface approximation , 2009, Microscopy research and technique.

[19]  Yong-Jun Kwon,et al.  Visual Genome-Wide RNAi Screening to Identify Human Host Factors Required for Trypanosoma cruzi Infection , 2011, PloS one.

[20]  George A. Stanciu,et al.  SUM-MODIFIED-LAPLACIAN FUSION METHODS EXPERIMENTED ON IMAGE STACKS OF PHOTONIC QUANTUM RING LASER DEVICES COLLECTED BY CONFOCAL SCANNING LASER MICROSCOPY , 2011 .

[21]  Tae-Sun Choi,et al.  Optimal depth estimation by combining focus measures using genetic programming , 2011, Inf. Sci..

[22]  Thomas A. Cleland,et al.  Chronic in vivo imaging in the mouse spinal cord using an implanted chamber , 2012, Nature Methods.

[23]  Tae-Sun Choi,et al.  Sampling for Shape from Focus in Optical Microscopy , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[24]  Johannes E. Schindelin,et al.  Fiji: an open-source platform for biological-image analysis , 2012, Nature Methods.

[25]  Yuan Yan Tang,et al.  Multi-focus image fusion based on the neighbor distance , 2013, Pattern Recognit..

[26]  Domenec Puig,et al.  Analysis of focus measure operators for shape-from-focus , 2013, Pattern Recognit..

[27]  Anne E Carpenter,et al.  Comparison of Methods for Image-Based Profiling of Cellular Morphological Responses to Small-Molecule Treatment , 2013, Journal of biomolecular screening.

[28]  Nadine Piat,et al.  Depth and Shape estimation from focus in scanning electron microscope for micromanipulation , 2013, 2013 International Conference on Control, Automation, Robotics and Embedded Systems (CARE).

[29]  Nathalie McCarthy,et al.  Extended two-photon microscopy in live samples with Bessel beams: steadier focus, faster volume scans, and simpler stereoscopic imaging , 2014, Front. Cell. Neurosci..

[30]  Hanchuan Peng,et al.  Extensible visualization and analysis for multidimensional images using Vaa3D , 2014, Nature Protocols.

[31]  Nathalie Spassky,et al.  Centriole amplification by mother and daughter centrioles differs in multiciliated cells , 2014, Nature.

[32]  Anne Vincent-Salomon,et al.  Unraveling the Role of Huntingtin in Breast Cancer Metastasis. , 2015, Journal of the National Cancer Institute.

[33]  Joachim Weickert,et al.  A focus fusion framework with anisotropic depth map smoothing , 2015, Pattern Recognit..

[34]  Philippe Isope,et al.  The Secreted Protein C1QL1 and Its Receptor BAI3 Control the Synaptic Connectivity of Excitatory Inputs Converging on Cerebellar Purkinje Cells. , 2015, Cell reports.

[35]  Christophe Zimmer,et al.  smiFISH and FISH-quant – a flexible single RNA detection approach with super-resolution capability , 2016, Nucleic acids research.

[36]  Michael Unser,et al.  DeconvolutionLab2: An open-source software for deconvolution microscopy. , 2017, Methods.

[37]  Auguste Genovesio,et al.  mTORC1 signaling and primary cilia are required for brain ventricle morphogenesis , 2017, Development.