The iRoCS Toolbox--3D analysis of the plant root apical meristem at cellular resolution.

To achieve a detailed understanding of processes in biological systems, cellular features must be quantified in the three-dimensional (3D) context of cells and organs. We described use of the intrinsic root coordinate system (iRoCS) as a reference model for the root apical meristem of plants. iRoCS enables direct and quantitative comparison between the root tips of plant populations at single-cell resolution. The iRoCS Toolbox automatically fits standardized coordinates to raw 3D image data. It detects nuclei or segments cells, automatically fits the coordinate system, and groups the nuclei/cells into the root's tissue layers. The division status of each nucleus may also be determined. The only manual step required is to mark the quiescent centre. All intermediate outputs may be refined if necessary. The ability to learn the visual appearance of nuclei by example allows the iRoCS Toolbox to be easily adapted to various phenotypes. The iRoCS Toolbox is provided as an open-source software package, licensed under the GNU General Public License, to make it accessible to a broad community. To demonstrate the power of the technique, we measured subtle changes in cell division patterns caused by modified auxin flux within the Arabidopsis thaliana root apical meristem.

ViBE-Z: a framework for 3D virtual colocalization analysis in zebrafish larval brains.

Precise three-dimensional (3D) mapping of a large number of gene expression patterns, neuronal types and connections to an anatomical reference helps us to understand the vertebrate brain and its development. We developed the Virtual Brain Explorer (ViBE-Z), a software that automatically maps gene expression data with cellular resolution to a 3D standard larval zebrafish (Danio rerio) brain. ViBE-Z enhances the data quality through fusion and attenuation correction of multiple confocal microscope stacks per specimen and uses a fluorescent stain of cell nuclei for image registration. It automatically detects 14 predefined anatomical landmarks for aligning new data with the reference brain. ViBE-Z performs colocalization analysis in expression databases for anatomical domains or subdomains defined by any specific pattern; here we demonstrate its utility for mapping neurons of the dopaminergic system. The ViBE-Z database, atlas and software are provided via a web interface.

Inversin relays Frizzled-8 signals to promote proximal pronephros development.

Mutations of inversin cause type II nephronophthisis, an infantile autosomal recessive disease characterized by cystic kidney disease and developmental defects. Inversin regulates Wnt signaling and is required for convergent extension movements during early embryogenesis. We now show that Inversin is essential for Xenopus pronephros formation, involving two distinct and opposing forms of cell movements. Knockdown of Inversin abrogated both proximal pronephros extension and distal tubule differentiation, phenotypes similar to that of Xenopus deficient in Frizzled-8. Exogenous Inversin rescued the pronephric defects caused by lack of Frizzled-8, indicating that Inversin acts downstream of Frizzled-8 in pronephros morphogenesis. Depletion of Inversin prevents the recruitment of Dishevelled in response to Frizzled-8 and impeded the accumulation of Dishevelled at the apical membrane of tubular epithelial cells in vivo. Thus, defective tubule morphogenesis seems to contribute to the renal pathology observed in patients with nephronophthisis type II.

Genetic and Methylation Analysis of CTNNB1 in Benign and Malignant Melanocytic Lesions.

Melanocytic neoplasms have been genetically characterized in detail during the last decade. Recurrent CTNNB1 exon 3 mutations have been recognized in the distinct group of melanocytic tumors showing deep penetrating nevus-like morphology. In addition, they have been identified in 1-2% of advanced melanoma. Performing a detailed genetic analysis of difficult-to-classify nevi and melanomas with CTNNB1 mutations, we found that benign tumors (nevi) show characteristic morphological, genetic and epigenetic traits, which distinguish them from other nevi and melanoma. Malignant CTNNB1-mutant tumors (melanomas) demonstrated a different genetic profile, instead grouping clearly with other non-CTNNB1 melanomas in methylation assays. To further evaluate the role of CTNNB1 mutations in melanoma, we assessed a large cohort of clinically sequenced melanomas, identifying 38 tumors with CTNNB1 exon 3 mutations, including recurrent S45 (n = 13, 34%), G34 (n = 5, 13%), and S27 (n = 5, 13%) mutations. Locations and histological subtype of CTNNB1-mutated melanoma varied; none were reported as showing deep penetrating nevus-like morphology. The most frequent concurrent activating mutations were BRAF V600 (n = 21, 55%) and NRAS Q61 (n = 13, 34%). In our cohort, four of seven (58%) and one of nine (11%) patients treated with targeted therapy (BRAF and MEK Inhibitors) or immune-checkpoint therapy, respectively, showed disease control (partial response or stable disease). In summary, CTNNB1 mutations are associated with a unique melanocytic tumor type in benign tumors (nevi), which can be applied in a diagnostic setting. In advanced disease, no clear characteristics distinguishing CTNNB1-mutant from other melanomas were observed; however, studies of larger, optimally prospective, cohorts are warranted.

In vivo noninvasive 4D pressure difference mapping in the human aorta: phantom comparison and application in healthy volunteers and patients.

In this work, we present a systematic phantom comparison and clinical application of noninvasive pressure difference mapping in the human aorta based on time-resolved 3D phase contrast data. Relative pressure differences were calculated based on integration and iterative refinement of pressure gradients derived from MR-based three-directional velocity vector fields (flow-sensitive 4D MRI with spatial/temporal resolution ∼ 2.1 mm(3)/40 ms) using the Navier-Stokes equation. After in vitro study using a stenosis phantom, time-resolved 3D pressure gradients were systematically evaluated in the thoracic aorta in a group of 12 healthy subjects and 6 patients after repair for aortic coarctation. Results from the phantom study showed good agreement with expected values and standard methods (Bernoulli). Data of healthy subjects showed good intersubject consistency and good agreement with the literature. In patients, pressure waveforms showed elevated peak values. Pressure gradients across the stenosis were compared with reference measurements from Doppler ultrasound. The MRI findings demonstrated a significant correlation (r = 0.96, P < 0.05) but moderate underestimation (14.7% ± 15.5%) compared with ultrasound when the maximum pressure difference for all possible paths connecting proximal and distal locations of the stenosis were used. This study demonstrates the potential of the applied approach to derive additional quantitative information such as pressure gradients from time-resolved 3D phase contrast MRI.

4D phase contrast MRI at 3 T: effect of standard and blood-pool contrast agents on SNR, PC-MRA, and blood flow visualization.

Time-resolved phase contrast (PC) MRI with velocity encoding in three directions (flow-sensitive four-dimensional MRI) can be employed to assess three-dimensional blood flow in the entire aortic lumen within a single measurement. These data can be used not only for the visualization of blood flow but also to derive additional information on vascular geometry with three-dimensional PC MR angiography (MRA). As PC-MRA is sensitive to available signal-to-noise ratio, standard and novel blood pool contrast agents may help to enhance PC-MRA image quality. In a group of 30 healthy volunteers, the influence of different contrast agents on vascular signal-to-noise ratio, PC-MRA quality, and subsequent three-dimensional stream-line visualization in the thoracic aorta was determined. Flow-sensitive four-dimensional MRI data acquired with contrast agent provided significantly improved signal-to-noise ratio in magnitude data and noise reduction in velocity data compared to measurements without contrast media. The agreement of three-dimensional PC-MRA with reference standard contrast-enhanced MRA was good for both contrast agents, with improved PC-MRA performance for blood pool contrast agent, particularly for the smaller supra-aortic branches. For three-dimensional flow visualization, a trend toward improved results for the data with contrast agent was observed.

Rotational invariance based on Fourier analysis in polar and spherical coordinates.

In this paper, polar and spherical Fourier analysis are defined as the decomposition of a function in terms of eigenfunctions of the Laplacian with the eigenfunctions being separable in the corresponding coordinates. The proposed transforms provide effective decompositions of an image into basic patterns with simple radial and angular structures. The theory is compactly presented with an emphasis on the analogy to the normal Fourier transform. The relation between the polar or spherical Fourier transform and the normal Fourier transform is explored. As examples of applications, rotation-invariant descriptors based on polar and spherical Fourier coefficients are tested on pattern classification problems.

Equivariant holomorphic filters for contour denoising and rapid object detection.

It is well known that linear filters are not powerful enough for many low-level image processing tasks. However, it is also very difficult to design robust nonlinear filters that respond exclusively to features of interest and that are, at the same time, equivariant with respect to translation and rotation. This paper proposes a new class of rotation-equivariant nonlinear filters that is based on the principle of group integration. These filters become efficiently computable by an iterative scheme based on repeated differentiation of products and summations of intermediate results. The relations of the proposed approach to Volterra filters and steerable filters are shown. In the context of detection problems, the filter may be interpreted as some kind of generalized Hough transform. The experiments show that the new filter can be used for enhancing noisy contours and rapid object detection in microscopical images. In the detection context, our experiments show that the proposed filter is definitely superior to alternative approaches, when high localization accuracy is required.

Complex derivative filters.

Steerable filters are a valuable tool for various low-level vision tasks. In this paper, we argue for the use of complex analysis in the context of 2-D steerable filters. In particular, we recommend the use of complex partial derivatives as a computational basis. Complex derivatives have a major advantage in comparison to real derivatives: they show a canonical rotation behavior, namely a rotation affects the derivative just by a multiplication with a complex unit number. So, the complex derivatives can be steered in a more elegant way and above that they are less expensive to compute. We present several analytical formulas for common and new filter kernels in terms of complex derivatives. Further we relate the complex derivatives of a Gaussian with the Gauss-Laguerre transform and show that the Gauss-Laguerre functions provide an optimal signal representation for local and smooth images. We discuss various finite difference schemes for the realization of the derivatives and use them in practice. In a first experiment, we use a newly introduced filter kernel for anisotropic blurring. The complex formalism offers an elegant way to locally adapt the shape and orientation of the kernel. Second, we use the proposed filters as matched filters to detect vessels in retinal images.

The writer independent online handwriting recognition system frog on hand and cluster generative statistical dynamic time warping.

In this paper, we give a comprehensive description of our writer-independent online handwriting recognition system frog on hand. The focus of this work concerns the presentation of the classification/training approach, which we call cluster generative statistical dynamic time warping (CSDTW). CSDTW is a general, scalable, HMM-based method for variable-sized, sequential data that holistically combines cluster analysis and statistical sequence modeling. It can handle general classification problems that rely on this sequential type of data, e.g., speech recognition, genome processing, robotics, etc. Contrary to previous attempts, clustering and statistical sequence modeling are embedded in a single feature space and use a closely related distance measure. We show character recognition experiments of frog on hand using CSDTW on the UNIPEN online handwriting database. The recognition accuracy is significantly higher than reported results of other handwriting recognition systems. Finally, we describe the real-time implementation of frog on hand on a Linux Compaq iPAQ embedded device.

Using snakes to detect the intimal and adventitial layers of the common carotid artery wall in sonographic images.

This study presents an innovative automatic system for detecting the intima-media complex of the far wall of the common carotid artery by applying the snake techniques. Cohen's snake was modified and some criteria were added for our applications. In addition, the oscillating problem of using snakes was solved by properly choosing the time step from analysis of the frequency response of the filters. A time-diminishing gravity window, external forces, and a cost function assist the snake in selecting the optimal shape of intimal and adventitia layers. We compared the proposed snake and ziplock snake with respect to the manual extraction contour. The results show that the system can automatically detect the intimal and adventitial layers without any manual correction.

RENNSH: a novel α-helix identification approach for intermediate resolution electron density maps.

Accurate identification of protein secondary structures is beneficial to understand three-dimensional structures of biological macromolecules. In this paper, a novel refined classification framework is proposed, which treats alpha-helix identification as a machine learning problem by representing each voxel in the density map with its Spherical Harmonic Descriptors (SHD). An energy function is defined to provide statistical analysis of its identification performance, which can be applied to all the α-helix identification approaches. Comparing with other existing α-helix identification methods for intermediate resolution electron density maps, the experimental results demonstrate that our approach gives the best identification accuracy and is more robust to the noise.

Fast rotation invariant 3D feature computation utilizing efficient local neighborhood operators.

We present a method for densely computing local rotation invariant image descriptors in volumetric images. The descriptors are based on a transformation to the harmonic domain, which we compute very efficiently via differential operators. We show that this fast voxelwise computation is restricted to a family of basis functions that have certain differential relationships. Building upon this finding, we propose local descriptors based on the Gaussian Laguerre and spherical Gabor basis functions and show how the coefficients can be computed efficiently by recursive differentiation. We exemplarily demonstrate the effectiveness of such dense descriptors in a detection and classification task on biological 3D images. In a direct comparison to existing volumetric features, among them 3D SIFT, our descriptors reveal superior performance.

Multiview deblurring for 3-D images from light-sheet-based fluorescence microscopy.

We propose an algorithm for 3-D multiview deblurring using spatially variant point spread functions (PSFs). The algorithm is applied to multiview reconstruction of volumetric microscopy images. It includes registration and estimation of the PSFs using irregularly placed point markers (beads). We formulate multiview deblurring as an energy minimization problem subject to L1-regularization. Optimization is based on the regularized Lucy-Richardson algorithm, which we extend to deal with our more general model. The model parameters are chosen in a profound way by optimizing them on a realistic training set. We quantitatively and qualitatively compare with existing methods and show that our method provides better signal-to-noise ratio and increases the resolution of the reconstructed images.

Harmonic filters for 3D multichannel data: rotation invariant detection of mitoses in colorectal cancer.

In this paper, we present a novel approach for a trainable rotation invariant detection of complex structures in 3D microscopic multichannel data using a nonlinear filter approach. The basic idea of our approach is to compute local features in a window around each 3D position and map these features by means of a nonlinear mapping onto new local harmonic descriptors of the local window. These local harmonic descriptors are then combined in a linear way to form the output of the filter. The optimal combination of the computed local harmonic descriptors is determined in previous training step, and allows the filter to be adapted to an arbitrary structure depending on the problem at hand. Our approach is not limited to scalar-valued images and can also be used for vector-valued (multichannel) images such as gradient vector flow fields. We present realizations of a scalar-valued and a vector-valued multichannel filter. Our proposed algorithm was quantitatively evaluated on colorectal cancer cell lines (cells grown under controlled conditions), on which we successfully detected complex 3D mitotic structures. For a qualitative evaluation we tested our algorithms on human 3D tissue samples of colorectal cancer. We compare our results with a steerable filter approach as well as a morphology-based approach.

Pericytes in the mature chorioallantoic membrane capillary plexus contain desmin and alpha-smooth muscle actin: relevance for non-sprouting angiogenesis.

The chicken chorioallantoic membrane (CAM) is a frequently used tissue for studying vascular growth and remodeling, notably non-sprouting angiogenesis by formation of transluminal pillars. Vascular pericytes have received increasing attention in the field of angiogenesis research and appear important for pillar growth. Our earlier observation that desmin (DES), but not alpha-smooth muscle actin (alphaSMA) was expressed in pericytes of the mature CAM capillary plexus after E12 was confirmed by others. However, in different species or vascular beds, either marker or both have been used to identify pericytes, raising the questions if (1) expression of these cytoskeletal proteins really was mutually exclusive; or (2) different types of pericytes existed in the same vascular bed. Using triple labeling with fluorochrome-conjugated markers Sambucus nigra agglutinin, DES or alphaSMA, and DNA-specific YoPro-1, we report here for the first time a delicate filamentous, circumferentially oriented alphaSMA pattern in periendothelial cells of the mature CAM capillary plexus, quite different from the coarser, axially oriented DES pattern. A new method for automatic classification of DNA-staining pattern was applied to compare nuclei of DES- or alphaSMA-positive cells. It predicted colocalisation of both proteins in most capillary pericytes, which was confirmed by double immunostaining for DES and alphaSMA. We conclude that (1) in contrast to published work, DES and alphaSMA are not mutually exclusive in most pericytes; (2) different types of pericytes may co-exist in the same vascular bed; (3) on average, one pericyte is associated with two transluminal pillars; (4) a novel imaging modality may be useful for cell identification in angiogenesis research and elsewhere.

On-line monitoring and identification of bioaerosols.

Fast analysis of bioaerosols in clean room environments is necessary in order to prevent contamination of pharmaceutical products, minimize machine downtimes, or both. The detection and identification of microbes will be carried out in several steps: After impaction of the aerosol on a surface, the particles are presorted with glancing light illumination and fluorescence imaging in order to distinguish between abiotic and biotic particles. Since only the biotic particles are of interest, the analysis time can be minimized due to reduction of the data set. The biotic particles are then analyzed further with Raman spectroscopy and identified with a support vector machine.

Chemotaxonomic identification of single bacteria by micro-Raman spectroscopy: application to clean-room-relevant biological contaminations.

Microorganisms, such as bacteria, which might be present as contamination inside an industrial food or pharmaceutical clean room process need to be identified on short time scales in order to minimize possible health hazards as well as production downtimes causing financial deficits. Here we describe the first results of single-particle micro-Raman measurements in combination with a classification method, the so-called support vector machine technique, allowing for a fast, reliable, and nondestructive online identification method for single bacteria.

Mind-body dualism and the compatibility of medical methods.

In this paper we analyse some misleading theses concerning the old controversy over the relation between mind and body presented in contemporary medical literature. We undertake an epistemological clarification of the axiomatic structure of medical methods. This clarification, in turn, requires a precise philosophical explanation of the presupposed concepts. This analysis will establish two results: (1) that the mind-body dualism cannot be understood as a kind of biological variation of the subject-object dichotomy in physics, and (2) that the thesis of the incompatibility between somatic and psychosomatic medicine held by naturalists and others lacks solid epistemological foundation.