5967
eng
reportzib
0
--
2016-06-15
--
NBLAST: Rapid, sensitive comparison of neuronal structure and construction of neuron family databases
Neural circuit mapping is generating datasets of 10,000s of labeled neurons. New computational tools are needed to search and organize these data. We present NBLAST, a sensitive and rapid algorithm, for measuring pairwise neuronal similarity. NBLAST considers both position and local geometry, decomposing neurons into short segments; matched segments are scored using a probabilistic scoring matrix defined by statistics of matches and non-matches.
We validated NBLAST on a published dataset of 16,129 single Drosophila neurons. NBLAST can distinguish neuronal types down to the finest level (single identified neurons) without a priori information. Cluster analysis of extensively studied neuronal classes identified new types and unreported topographical features. Fully automated clustering organized the validation dataset into 1052 clusters, many of which map onto previously described neuronal types. NBLAST supports additional query types including searching neurons against transgene expression patterns. Finally we show that NBLAST is effective with data from other invertebrates and zebrafish.
1438-0064
urn:nbn:de:0297-zib-59672
10.1016/j.neuron.2016.06.012
appeared also as bioRxiv preprint http://dx.doi.org/10.1101/006346 and in revised form in Neuron
Marta Costa
Steffen Prohaska
James D. Manton
Aaron D. Ostrovsky
Steffen Prohaska
Gregory S.X.E. Jefferis
ZIB-Report
16-34
eng
uncontrolled
neuroinformatics
eng
uncontrolled
NBLAST
eng
uncontrolled
neuron similarity
eng
uncontrolled
cell type
eng
uncontrolled
clustering
Computer Applications
INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY
COMPUTER SCIENCE (For papers involving machine computations and programs in a specific mathematical area, see Section -04 in that area)
BIOLOGY AND OTHER NATURAL SCIENCES
Visual Data Analysis
Prohaska, Steffen
no-project
Visual and Data-centric Computing
https://opus4.kobv.de/opus4-zib/files/5967/zibreport-16-34_v1.pdf
1425
2011
eng
reportzib
0
2011-11-05
2011-11-05
--
Level of Detail for Trees Using Clustered Ellipsoids
We present a level of detail method for trees based on ellipsoids and lines. We leverage the Expectation Maximization algorithm with a Gaussian Mixture Model to create a hierarchy of high-quality leaf clusterings, while the branches are simplified using agglomerative bottom-up clustering to preserve the connectivity. The simplification runs in a preprocessing step and requires no human interaction. For a fly by over and through a scene of 10k trees, our method renders on average at 40 ms/frame, up to 6 times faster than billboard clouds with comparable artifacts.
1438-0064
11-41
urn:nbn:de:0297-zib-14251
no
Malte Clasen
Steffen Prohaska
Philip Paar
Steffen Prohaska
ZIB-Report
11-41
eng
uncontrolled
level of detail
eng
uncontrolled
rendering
eng
uncontrolled
natural scene
eng
uncontrolled
Gaussian mixture model
Computing Methodologies
INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY
NUMERICAL ANALYSIS
COMPUTER SCIENCE (For papers involving machine computations and programs in a specific mathematical area, see Section -04 in that area)
Visual Data Analysis
Image Analysis in Biology and Materials Science
Prohaska, Steffen
Visual and Data-centric Computing
https://opus4.kobv.de/opus4-zib/files/1425/zibreport.pdf
6231
2017
eng
reportzib
0
--
2017-03-24
--
Monte-Carlo-based inversion scheme for 3D quantitative photoacoustic tomography
The goal of quantitative photoacoustic tomography (qPAT) is to recover maps of the chromophore distributions from multiwavelength images of the initial pressure. Model-based inversions that incorporate the physical processes underlying the photoacoustic (PA) signal generation represent a promising approach. Monte-Carlo models of the light transport are computationally expensive, but provide accurate fluence distributions predictions, especially in the ballistic and quasi-ballistic regimes. Here, we focus on the inverse problem of 3D qPAT of blood oxygenation and investigate the application of the Monte-Carlo method in a model-based inversion scheme. A forward model of the light transport based on the MCX simulator and acoustic propagation modeled by the k-Wave toolbox was used to generate a PA image data set acquired in a tissue phantom over a planar detection geometry. The combination of the optical and acoustic models is shown to account for limited-view artifacts. In addition, the errors in the fluence due to, for example, partial volume artifacts and absorbers immediately adjacent to the region of interest are investigated. To accomplish large-scale inversions in 3D, the number of degrees of freedom is reduced by applying image segmentation to the initial pressure distribution to extract a limited number of regions with homogeneous optical parameters. The absorber concentration in the tissue phantom was estimated using a coordinate descent parameter search based on the comparison between measured and modeled PA spectra. The estimated relative concentrations using this approach lie within 5 % compared to the known concentrations. Finally, we discuss the feasibility of this approach to recover the blood oxygenation from experimental data.
1438-0064
urn:nbn:de:0297-zib-62318
10.1117/12.2251945
Appeared in: Proc. SPIE 10064, Photons Plus Ultrasound: Imaging and Sensing 2017, 100645J (March 23, 2017)
Bernhard Kaplan
Bernhard Kaplan
Jan Laufer
Steffen Prohaska
Jens Buchmann
ZIB-Report
17-04
eng
uncontrolled
quantitative photoacoustic tomography
eng
uncontrolled
model-based inversion
eng
uncontrolled
oxygen saturation
eng
uncontrolled
chromophore concentration
eng
uncontrolled
photoacoustic imaging
eng
uncontrolled
Monte Carlo methods for light transport
eng
uncontrolled
boundary conditions
eng
uncontrolled
coordinate search
Computer Applications
INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY
COMPUTER SCIENCE (For papers involving machine computations and programs in a specific mathematical area, see Section -04 in that area)
Visual Data Analysis
Prohaska, Steffen
dfg-photom
Visual and Data-centric Computing
https://opus4.kobv.de/opus4-zib/files/6231/zib_report_qpat.pdf
5295
eng
reportzib
0
--
2014-10-28
--
Automated stitching of microtubule centerlines across serial electron tomograms
Tracing microtubule centerlines in serial section electron tomography requires microtubules to be stitched across sections, that is lines from different sections need to be aligned, endpoints need to be matched at section boundaries to establish a correspondence between neighboring sections, and corresponding lines need to be connected across multiple sections. We present computational methods for these tasks: 1) An initial alignment is computed using a distance compatibility graph. 2) A fine alignment is then computed with a probabilistic variant of the iterative closest points algorithm, which we extended to handle the orientation of lines by introducing a periodic random variable to the probabilistic formulation. 3) Endpoint correspondence is established by formulating a matching problem in terms of a Markov random field and computing the best matching with belief propagation. Belief propagation is not generally guaranteed to converge to a minimum. We show how convergence can be achieved, nonetheless, with minimal manual input. In addition to stitching microtubule centerlines, the correspondence is also applied to transform and merge the electron tomograms. We applied the proposed methods to samples from the mitotic spindle in C. elegans, the meiotic spindle in X. laevis, and sub-pellicular microtubule arrays in T. brucei. The methods were able to stitch microtubules across section boundaries in good agreement with experts’ opinions for the spindle samples. Results, however, were not satisfactory for the microtubule arrays. For certain experiments, such as an analysis of the spindle, the proposed methods can replace manual expert tracing and thus enable the analysis of microtubules over long distances with reasonable manual effort.
1438-0064
urn:nbn:de:0297-zib-52958
10.1371/journal.pone.0113222
published in PLoS ONE
Britta Weber
Steffen Prohaska
Erin M. Tranfield
Johanna L. Höög
Daniel Baum
Claude Antony
Tony Hyman
Jean-Marc Verbavatz
Steffen Prohaska
ZIB-Report
14-41
eng
uncontrolled
electron tomography
eng
uncontrolled
microtubules
eng
uncontrolled
serial sectioning
eng
uncontrolled
image analysis
eng
uncontrolled
geometry reconstruction
eng
uncontrolled
image and geometry alignment
eng
uncontrolled
point correspondence
Applications
Biology and genetics (REVISED)
Cell processes
PROBABILITY THEORY AND STOCHASTIC PROCESSES (For additional applications, see 11Kxx, 62-XX, 90-XX, 91-XX, 92-XX, 93-XX, 94-XX)
COMPUTER SCIENCE (For papers involving machine computations and programs in a specific mathematical area, see Section -04 in that area)
BIOLOGY AND OTHER NATURAL SCIENCES
Visual Data Analysis
Image Analysis in Biology and Materials Science
Baum, Daniel
Prohaska, Steffen
MICROTUBULES
SPINDLE
Visual and Data-centric Computing
https://opus4.kobv.de/opus4-zib/files/5295/zibreport-14-41_v1.pdf
7439
eng
reportzib
0
--
2019-08-14
--
Serial synapse formation through filopodial competition for synaptic seeding factors
Following axon pathfinding, growth cones transition from stochastic filopodial exploration to the formation of a limited number of synapses. How the interplay of filopodia and synapse assembly ensures robust connectivity in the brain has remained a challenging problem. Here, we developed a new 4D analysis method for filopodial dynamics and a data-driven computational model of synapse formation for R7 photoreceptor axons in developing Drosophila brains. Our live data support a 'serial synapse formation' model, where at any time point only a single 'synaptogenic' filopodium suppresses the synaptic competence of other filopodia through competition for synaptic seeding factors. Loss of the synaptic seeding factors Syd-1 and Liprin-α leads to a loss of this suppression, filopodial destabilization and reduced synapse formation, which is sufficient to cause the destabilization of entire axon terminals. Our model provides a filopodial 'winner-takes-all' mechanism that ensures the formation of an appropriate number of synapses.
1438-0064
urn:nbn:de:0297-zib-74397
10.1016/j.devcel.2019.06.014
Appeared in: Developmental Cell, 50(4), pp. 447-461, 2019
M. Neset Özel
Josephine Brummer
Abhishek Kulkarni
Amr Hasan
Josephine Brummer
Marian Moldenhauer
Ilsa-Maria Daumann
Heike Wolfenberg
Vincent J. Dercksen
F. Ridvan Kiral
Martin Weiser
Steffen Prohaska
Max von Kleist
Peter Robin Hiesinger
ZIB-Report
19-45
eng
uncontrolled
filopodia
eng
uncontrolled
growth cone dynamics
eng
uncontrolled
brain wiring
eng
uncontrolled
2-photon microscopy
eng
uncontrolled
model
Computing Methodologies
Computer Applications
INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY
PROBABILITY THEORY AND STOCHASTIC PROCESSES (For additional applications, see 11Kxx, 62-XX, 90-XX, 91-XX, 92-XX, 93-XX, 94-XX)
COMPUTER SCIENCE (For papers involving machine computations and programs in a specific mathematical area, see Section -04 in that area)
BIOLOGY AND OTHER NATURAL SCIENCES
Numerical Mathematics
Visual Data Analysis
Prohaska, Steffen
Weiser, Martin
FU-Images
GC-Dynamics
BrainWiring
Visual and Data-centric Computing
https://opus4.kobv.de/opus4-zib/files/7439/zibreport-19-45_v1.pdf