™Huygens Confocal Deconvolution Software
The gold standard in removing noise and blur, and improving resolution
Huygens true deconvolution for single point-scanning Confocal Microscope images offers unprecedented results. Look for yourself what can be achieved by requesting a free trial! We promise you a significant improvement in object resolution in x, y and z as well as an increase in object signal and correction of noise. As a result, images will be easier to segment for optimal visualization and analysis. The gain in signal and correction of noise also allow you to image faster, causing less phototoxicity and bleaching. Huygens offers state-of-the art implementations of the Classic Maximum Likelihood Estimation (CMLE) and the Good's roughness Maximum Likelihood Estimation (GMLE) algorithms, which work very fast and efficiently on noisy image data.
Image description Maximum Intensity Projection of a confocal image before (right) and after (left) Huygens Deconvolution. Image shows basal bodies of the cilia in a paramecium. Data was provided by A. Aubusson-Fleury, CNRS, Gif sur Yvette, Paris.
All Microscope Brands
120nm Resolution
Most advanced algorithms
Testimonials
Our confocal microscopy users are really impressed by the program! We find it very important for our research with yeast cells and bacteria
PD Dr. Christina Schlatterer, research manager at AG Deuerling (molecular biology), University of Konstanz, Germany.
Researchers who use Huygens at the facility to enhance their confocal data are very much impressed by the results.
Dr. Ulrike Engel, scientific director of the Nikon Imaging Centre, University of Heidelberg, Germany.
Faster imaging
A key limitation of confocal imaging is the long acquisition time. This time can be strongly decreased when using Huygens Deconvolution after image acquisition. Huygens Deconvolution decreases noise while increasing the object signal. Clear images can therefore be recovered even when the raw data has a low signal-to-noise ratio (SNR). Since a low signal is already sufficient, the exposure time can be decreased. It then takes less time to image the entire sample.
Click here for more info on restoring noisy data
Image description Maximum Intensity Projection of a noisy confocal image before (left) and after (right) Huygens Deconvolution. Data acquired with low signal-to-noise ratio (SNR) to demonstrate noise correction through Huygens Deconvolution. Data courtesy of Dr. Pawel Pasierbek, BioOptics IMP Vienna, Austria
See deeper
Microscopy images are aberrated with respect to the objects under the microscope. These aberrations are not constant throughout the entire image: typically, the image quality gets progressively worse as you move deeper within the sample. This is due to Spherical Aberrations caused by a mismatch between the refractive indices of the sample and of the lens medium. Huygens Deconvolution accurately calculates the function describing the aberrations in the image, the so-called Point Spread Function (PSF), in a depth-dependent manner. It then uses this depth-dependent PSF to achieve consistant restoration quality over the entire depth range.
Click here for more information on the theoretical PSF
Image description Theoretical PSFs calculated by Huygens based on the distance to the coverslip. Huygens Deconvolution is performed in a depth-dependent manner to ensure consistent restoration quality throughout the image. Distances between PSFs were decreased for visualization purposes.
Use in research
Walker C.K, Greathouse K.M, Boros B.D, et al. (2021). Dendritic Spine Remodeling and Synaptic Tau Levels in PS19 Tauopathy Mice. Confocal stacks of dendrites were deconvolved using Huygens Professional. Neuroscience Volume 455, 10 February 2021, Pages 195-211
Bhukel, A., Beuschel, C. B., Maglione, et al. (2019). Autophagy within the mushroom body protects from synapse aging in a non-cell autonomous manner. Huygens was used for confocal deconvolution Nature communications, 10(1), 1318.
For more, see Scientific Publications
Related Products
The best deconvolution results can be achieved by using a measured PSF extracted with the Huygens PSF Distiller. After deconvolution, images can be used for reliable image analysis, for example colocalization analysis.
PSF Distiller Colocalization Analyzer
More information
Introduction to deconvolution Huygens Deconvolution Restoration examples
Huygens Confocal deconvolution gallery
Image of DAPI (Red) and mab22C10 (Green) staining in larval brain of Drosophila melanogaster. The image was captured using Leica SP5II confocal microscope. Image was kindly provided by Dr. Anand Krishna Tiwari, Indian Institute of Advanced Studies, India.
See more: Images in the field of Neurosciences
Yeast organelle transport. Time series acquisition, Single point-scanning Confocal. Late-Golgi marker Sec7-DsRed, Early Golgi marker Cog1-GFP. Perfectly acquired, but noisy confocal time series of low abundance proteins in yeast endosomal and Golgi system allows accurate object analysis after deconvolution with Huygens. Image kindly provided by Prof. Benjamin S. Glick, MGCB, University of Chicago, United States.
See more: Images in the field of Cell Biology
Image shows the remarkable complexity of the actin filament network in primary mouse embryonic fibroblasts (pMEF) null for the actin regulatory proteins Tm5NM1/2. Actin filaments are visualised by phalloidin. Confocal image (N.A1.4. 100x) was deconvolved and visualised with Huygens Professional. Image kindly provided by Mr. Howard Vindin. Cellular & Genetic Medicine Unit, School of Medical Sciences, University of New South Wales, Australia.
See more: Images in the field of Developmental Biology
A series of developing Drosophila oocytes (egg-chambers to be precise). A Z-stack of 116 optical sections was taken on a Leica SP8 Laser scanning confocal microscope with a 63x 1.4NA objective. Actin (in yellow) is stained with rhodamin phalloidin and the nuclear envelopes of the so -called nurse cells are labeled with autofluorescence of GFP-Tm1 (green). HRM was used to deconcolve the raw image. Image kindly provided by Dr. Imre Gaspar, Developmental Biology Unit, EMBL Heidelberg, Germany.
See more: Images in the field of Developmental Biology