We present a novel approach to the problem of neuron segmentation in image volumes acquired by an electron microscopy. Existing methods, such as agglomerative or correlation clustering, rely solely ...on boundary evidence and have problems where such an evidence is lacking (e.g., incomplete staining) or ambiguous (e.g., co-located cell and mitochondria membranes). We investigate if these difficulties can be overcome by means of sparse region appearance cues that differentiate between pre- and postsynaptic neuron segments in mammalian neural tissue. We combine these cues with the traditional boundary evidence in the asymmetric multiway cut (AMWC) model, which simultaneously solves the partitioning and the semantic region labeling problems. We show that AMWC problems over superpixel graphs can be solved to global optimality with a cutting plane approach, and that the introduction of semantic class priors leads to significantly better segmentations.
The program SEAL is suited to describe the electrostatic, steric, hydrophobic, and hydrogen bond donor and acceptor similarity of different molecules in a quantitative manner. Similarity scores AF ...can be calculated for pairs of molecules, using either a certain molecular property or a sum of weighted properties. Alternatively, their mutual similarity can be derived from distances d or covariances c between SEAL-based property fields that are calculated in a regular grid. For a set of N chemically related molecules, such values form an N x N similarity matrix which can be correlated with biological activities, using either regression analysis and an appropriate variable selection procedure or partial least-squares (PLS) analysis. For the Cramer steroid data set, the test set predictivities (r2pred = 0.53-0.84) of different PLS models, based on a weighted sum of molecular properties, are superior to published results of CoMFA and CoMSIA studies (r2pred = 0.31-0.40), regardless of whether a common alignment or individual, pairwise alignments of all molecules are used in the calculation of the similarity matrices. Training and test set selections have a significant influence on the external predictivities of the models. Although the SEAL similarity score between two molecules is a single number, its value is based on the 3D properties of both molecules. The term 3D quantitative similarity-activity analyses (3D QSiAR) is proposed for approaches which correlate 3D structure-derived similarity matrices with biological activities.
Summary
The development of realistic neuroanatomical models of peripheral nerves for simulation purposes requires the reconstruction of the morphology of the myelinated fibres in the nerve, including ...their nodes of Ranvier. Currently, this information has to be extracted by semimanual procedures, which severely limit the scalability of the experiments.
In this contribution, we propose a supervised machine learning approach for the detailed reconstruction of the geometry of fibres inside a peripheral nerve based on its high‐resolution serial section images. Learning from sparse expert annotations, the algorithm traces myelinated axons, even across the nodes of Ranvier. The latter are detected automatically.
The approach is based on classifying the myelinated membranes in a supervised fashion, closing the membrane gaps by solving an assignment problem, and classifying the closed gaps for the nodes of Ranvier detection.
The algorithm has been validated on two very different datasets: (i) rat vagus nerve subvolume, SBFSEM microscope, 200 × 200 × 200 nm resolution, (ii) rat sensory branch subvolume, confocal microscope, 384 × 384 × 800 nm resolution. For the first dataset, the algorithm correctly reconstructed 88% of the axons (241 out of 273) and achieved 92% accuracy on the task of Ranvier node detection. For the second dataset, the gap closing algorithm correctly closed 96.2% of the gaps, and 55% of axons were reconstructed correctly through the whole volume. On both datasets, training the algorithm on a small data subset and applying it to the full dataset takes a fraction of the time required by the currently used semiautomated protocols. Our software, raw data and ground truth annotations are available at http://hci.iwr.uni‐heidelberg.de/Benchmarks/. The development version of the code can be found at https://github.com/RWalecki/ATMA.
Lay Description
3D Electron Microscopy allows neuroscientists to take volumetric images of peripheral nerve pieces. By analyzing the images, we can thus create a detailed picture of the nerve anatomy and reconstruct the shape of axons inside the nerve. However, in order to build such a detailed 3D model, axons in each image have to be separated from the background and correspondences have to be established between pieces of the same axon across images. Our contribution proposes a method, which performs these two steps automatically, based on user annotations in a small sub‐volume of the data.
In surface characterization tasks, the material ratio function is one of the most important tools and the basis for many parameters defined in international standards. Yet, the material ratio does ...not contain information on spatial features. In this contribution, characterizing functions that generalize the material ratio function approach to include spatial features are presented. These functions can be related to properties such as roughness, fluid flow or connectedness of peaks. In a second step, two classes of surface models for which these characterizing functions can be calculated analytically are presented. By comparing measured and analytically calculated functions, one can estimate model parameters from the characterizing functions, which then serve as simplified surface descriptors. Finally, the capabilities of the introduced methods are illustrated by means of simulations and comparison with experiments.
A popular technique to monitor laser welding processes is to record laser-induced plasma radiation with a highspeed camera. The recorded sequences are analyzed using pattern recognition systems. ...Since the raw data are too high dimensional to allow for an efficient learning, dimension reduction is necessary. The most common technique for dimension reduction in laser welding applications is to use geometric information of segmented objects. In contrast, we propose to adapt ideas from face recognition and to employ appearance-based features to describe the relevant characteristics of the recorded images. The classification performance of geometric and appearance-based features is compared on a representative data set from an industrial laser welding application. Hidden Markov models are used to capture the temporal dependences and to perform the classification of unlabeled sequences into an error-free and an erroneous class. We demonstrate that a classification system based on appearance-based features can outperform geometric features.
The objectives of this study were to assess Candida spp. distribution and antifungal resistance of candidaemia across Europe. Isolates were collected as part of the third ECMM Candida European ...multicentre observational study, conducted from 01 to 07-07-2018 to 31-03-2022. Each centre (maximum number/country determined by population size) included ∼10 consecutive cases. Isolates were referred to central laboratories and identified by morphology and MALDI-TOF, supplemented by ITS-sequencing when needed. EUCAST MICs were determined for five antifungals. fks sequencing was performed for echinocandin resistant isolates. The 399 isolates from 41 centres in 17 countries included C. albicans (47.1%), C. glabrata (22.3%), C. parapsilosis (15.0%), C. tropicalis (6.3%), C. dubliniensis and C. krusei (2.3% each) and other species (4.8%). Austria had the highest C. albicans proportion (77%), Czech Republic, France and UK the highest C. glabrata proportions (25–33%) while Italy and Turkey had the highest C. parapsilosis proportions (24–26%). All isolates were amphotericin B susceptible. Fluconazole resistance was found in 4% C. tropicalis, 12% C. glabrata (from six countries across Europe), 17% C. parapsilosis (from Greece, Italy, and Turkey) and 20% other Candida spp. Four isolates were anidulafungin and micafungin resistant/non-wild-type and five resistant to micafungin only. Three/3 and 2/5 of these were sequenced and harboured fks-alterations including a novel L657W in C. parapsilosis. The epidemiology varied among centres and countries. Acquired echinocandin resistance was rare but included differential susceptibility to anidulafungin and micafungin, and resistant C. parapsilosis. Fluconazole and voriconazole cross-resistance was common in C. glabrata and C. parapsilosis but with different geographical prevalence.
•Candidaemia epidemiology differs notably across 41 centres in 17 countries.•C. albicans proportions varied from 77% in Austria to 36% in Turkey.•Acquired fluconazole resistance emerges in C. parapsilosis in southern Europe.•A novel echinocandin resistance mutation and MDR was demonstrated in C. parapsilosis.•Antifungal stewardship and infection control is of utmost importance.
Dynamic contrast-enhanced magnetic resonance (DCE-MR) imaging can be used to study microvascular structure in vivo by monitoring the abundance of an injected diffusible contrast agent over time. The ...resulting spatially resolved intensity-time curves are usually interpreted in terms of kinetic parameters obtained by fitting a pharmacokinetic model to the observed data. Least squares estimates of the highly nonlinear model parameters, however, can exhibit high variance and can be severely biased. As a remedy, we bring to bear spatial prior knowledge by means of a generalized Gaussian Markov random field (GGMRF). By using information from neighboring voxels and computing the maximum a posteriori solution for entire parameter maps at once, both bias and variance of the parameter estimates can be reduced thus leading to smaller root mean square error (RMSE). Since the number of variables gets very big for common image resolutions, sparse solvers have to be employed. To this end, we propose a generalized iterated conditional modes (ICM) algorithm operating on blocks instead of sites which is shown to converge considerably faster than the conventional ICM algorithm. Results on simulated DCE-MR images show a clear reduction of RMSE and variance as well as, in some cases, reduced estimation bias. The mean residual bias (MRB) is reduced on the simulated data as well as for all 37 patients of a prostate DCE-MRI dataset. Using the proposed algorithm, average computation times only increase by a factor of 1.18 (871 ms per voxel) for a Gaussian prior and 1.51 (1.12 s per voxel) for an edge-preserving prior compared to the single voxel approach (740 ms per voxel).
Optimal lattices for sampling Kunsch, H.R.; Agrell, E.; Hamprecht, F.A.
IEEE transactions on information theory,
02/2005, Letnik:
51, Številka:
2
Journal Article
Recenzirano
Odprti dostop
The generalization of the sampling theorem to multidimensional signals is considered, with or without bandwidth constraints. The signal is modeled as a stationary random process and sampled on a ...lattice. Exact expressions for the mean-square error of the best linear interpolator are given in the frequency domain. Moreover, asymptotic expansions are derived for the average mean-square error when the sampling rate tends to zero and infinity, respectively. This makes it possible to determine the optimal lattices for sampling. In the low-rate sampling case, or equivalently for rough processes, the optimal lattice is the one which solves the packing problem, whereas in the high-rate sampling case, or equivalently for smooth processes, the optimal lattice is the one which solves the dual packing problem. In addition, the best linear interpolation is compared with ideal low-pass filtering (cardinal interpolation).
Due to the relative transparency of its embryos and larvae, the zebrafish is an ideal model organism for bioimaging approaches in vertebrates. Novel microscope technologies allow the imaging of ...developmental processes in unprecedented detail, and they enable the use of complex image-based read-outs for high-throughput/high-content screening. Such applications can easily generate Terabytes of image data, the handling and analysis of which becomes a major bottleneck in extracting the targeted information. Here, we describe the current state of the art in computational image analysis in the zebrafish system. We discuss the challenges encountered when handling high-content image data, especially with regard to data quality, annotation, and storage. We survey methods for preprocessing image data for further analysis, and describe selected examples of automated image analysis, including the tracking of cells during embryogenesis, heartbeat detection, identification of dead embryos, recognition of tissues and anatomical landmarks, and quantification of behavioral patterns of adult fish. We review recent examples for applications using such methods, such as the comprehensive analysis of cell lineages during early development, the generation of a three-dimensional brain atlas of zebrafish larvae, and high-throughput drug screens based on movement patterns. Finally, we identify future challenges for the zebrafish image analysis community, notably those concerning the compatibility of algorithms and data formats for the assembly of modular analysis pipelines.
In industrial surface characterization tasks, tactile profile measurement instruments are still the dominating tool for measuring surface roughness. Among the parameters for quantifying surface ...roughness based on tactile profile sections,
R
z
and
R
a
are the most popular ones. Nevertheless, it is widely recognized that profile parameters in general should be replaced by parameters which use the whole surface information made available by state-of-the-art 3D-measuring devices like white-light interferometry. In this contribution, a natural and easily interpretable extension of the roughness characteristic
R
z
for 3D data, called
S
z
morph
, is proposed and its intimate relation to the volume scale function, a fractal characteristic recently proposed for standardization, is shown. The derivation shows that while the slope of the volume scale function gives an indication of local fractal dimension, its absolute value is closely related to traditional definitions of surface roughness. The proposed characteristic ignores surface directionality and as such is applicable to directional and non-directional surfaces. Experimental results for three different technical surfaces demonstrate the very good correlation of
S
z
morph
with the original parameter
R
z
.
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