Image Processing Challenges in the Creation of Spatiotemporal Gene Expression Atlases of Developing Embryos

To properly understand and model animal embryogenesis it is crucial to obtain detailed measurements, both in time and space, about their gene expression domains and cell dynamics. Such challenge has been confronted in recent years by a surge of atlases which integrate a statistically relevant number of different individuals to get robust, complete information about their spatiotemporal locations of gene patterns. This paper will discuss the fundamental image analysis strategies required to build such models and the most common problems found along the way. We also discuss the main challenges and future goals in the field.

Image Processing Challenges in the Creation of Spatiotemporal Gene Expression Atlases of Developing Embryos

To properly understand and model animal embryogenesis it is crucial to obtain detailed measurements, both in time and space, about their gene expression domains and cell dynamics. Such challenge has been confronted in recent years by a surge of atlases which integrate a statistically relevant number of different individuals to get robust, complete information about their spatiotemporal locations of gene patterns. This paper will discuss the fundamental image analysis strategies required to build such models and the most common problems found along the way. We also discuss the main challenges and future goals in the field.

Experimental analysis of the breakage of a liquid bridge under microgravity conditions

The experimental results obtained in experiment “STACO” made on board the Spacelab D-2 are re-visited, with image-analysis tools not then available. The configuration consisted of a liquid bridge between two solid supporting discs. An expected breakage occurred during the experiment. The recorded images are analysed and the measured behaviour compared with the results of a three dimensional model of the liquid dynamics, obtaining a much better fit than with linear models

Automatic motion compensation of free breathing acquired myocardial perfusion data by using independent component analysis

Images acquired during free breathing using first-pass gadolinium-enhanced myocardial perfusion magnetic resonance imaging (MRI) exhibit a quasiperiodic motion pattern that needs to be compensated for if a further automatic analysis of the perfusion is to be executed. In this work, we present a method to compensate this movement by combining independent component analysis (ICA) and image registration: First, we use ICA and a time?frequency analysis to identify the motion and separate it from the intensity change induced by the contrast agent. Then, synthetic reference images are created by recombining all the independent components but the one related to the motion. Therefore, the resulting image series does not exhibit motion and its images have intensities similar to those of their original counterparts. Motion compensation is then achieved by using a multi-pass image registration procedure. We tested our method on 39 image series acquired from 13 patients, covering the basal, mid and apical areas of the left heart ventricle and consisting of 58 perfusion images each. We validated our method by comparing manually tracked intensity profiles of the myocardial sections to automatically generated ones before and after registration of 13 patient data sets (39 distinct slices). We compared linear, non-linear, and combined ICA based registration approaches and previously published motion compensation schemes. Considering run-time and accuracy, a two-step ICA based motion compensation scheme that first optimizes a translation and then for non-linear transformation performed best and achieves registration of the whole series in 32 ± 12 s on a recent workstation. The proposed scheme improves the Pearsons correlation coefficient between manually and automatically obtained time?intensity curves from .84 ± .19 before registration to .96 ± .06 after registration

New perspectives on quantitative textural analysis

Process mineralogy provides the mineralogical information required by geometallurgists to address the inherent variation of geological data. The successful benefitiation of ores mostly depends on the ability of mineral processing to be efficiently adapted to the ore characteristics, being liberation one of the most relevant mineralogical parameters. The liberation characteristics of ores are intimately related to mineral texture. Therefore, the characterization of liberation necessarily requieres the identification and quantification of those textural features with a major bearing on mineral liberation. From this point of view grain size, bonding between mineral grains and intergrowth types are considered as the most influential textural attributes. While the quantification of grain size is a usual output of automated current technologies, information about grain boundaries and intergrowth types is usually descriptive and difficult to quantify to be included in the geometallurgical model. Aiming at the systematic and quantitative analysis of the intergrowth type within mineral particles, a new methodology based on digital image analysis has been developed. In this work, the ability of this methodology to achieve a more complete characterization of liberation is explored by the analysis of chalcopyrite in the rougher concentrate of the Kansanshi copper-gold mine (Zambia). Results obtained show that the method provides valuable textural information to achieve a better understanding of mineral behaviour during concentration processes. The potential of this method is enhanced by the fact that it provides data unavailable by current technologies. This opens up new perspectives on the quantitative analysis of mineral processing performance based on textural attributes.

Improving parameters selection of a seeded region growing method for multiband image segmentation

In the last decade, Object Based Image Analysis (OBIA) has been accepted as an effective method for processing high spatial resolution multiband images. This image analysis method is an approach that starts with the segmentation of the image. Image segmentation in general is a procedure to partition an image into homogenous groups (segments). In practice, visual interpretation is often used to assess the quality of segmentation and the analysis relies on the experience of an analyst. In an effort to address the issue, in this study, we evaluate several seed selection strategies for an automatic image segmentation methodology based on a seeded region growing-merging approach. In order to evaluate the segmentation quality, segments were subjected to spatial autocorrelation analysis using Moran's I index and intra-segment variance analysis. We apply the algorithm to image segmentation using an aerial multiband image.

Quantitative analysis of morphological changes in yeast colonies growing on solid medium: the eccentricity and Fourier indices

The colony shape of four yeast species growing on agar medium wasmeasured for 116 days by image analysis. Initially, all the colonies are circular, with regular edges. The loss of circularity can be quantitatively estimated by the eccentricity index, Ei, calculated as the ratio between their orthogonal vertical and horizontal diameters. Ei can increase from 1 (complete circularity) to a maximum of 1.17–1.30, depending on the species. One colony inhibits its neighbour only when it has reached a threshold area. Then, Ei of the inhibited colony increases proportionally to the area of the inhibitory colony. The initial distance between colonies affects those threshold values but not the proportionality, Ei/area; this inhibition affects the shape but not the total surface of the colony. The appearance of irregularities in the edges is associated, in all the species, not with age but with nutrient exhaustion. The edge irregularity can be quantified by the Fourier index, Fi, calculated by the minimum number of Fourier coefficients that are needed to describe the colony contour with 99% fitness. An ad hoc function has been developed in Matlab v. 7.0 to automate the computation of the Fourier coefficients. In young colonies, Fi has a value between 2 (circumference) and 3 (ellipse). These values are maintained in mature colonies of Debaryomyces, but can reach values up to 14 in Saccharomyces.All the species studied showed the inhibition of growth in facing colony edges, but only three species showed edge irregularities associated with substrate exhaustion. Copyright © 2014 John Wiley & Sons, Ltd.

A study of feature combination for vehicle detection based on image processing

Video analytics play a critical role in most recent traffic monitoring and driver assistance systems. In this context, the correct detection and classification of surrounding vehicles through image analysis has been the focus of extensive research in the last years. Most of the pieces of work reported for image-based vehicle verification make use of supervised classification approaches and resort to techniques, such as histograms of oriented gradients (HOG), principal component analysis (PCA), and Gabor filters, among others. Unfortunately, existing approaches are lacking in two respects: first, comparison between methods using a common body of work has not been addressed; second, no study of the combination potentiality of popular features for vehicle classification has been reported. In this study the performance of the different techniques is first reviewed and compared using a common public database. Then, the combination capabilities of these techniques are explored and a methodology is presented for the fusion of classifiers built upon them, taking into account also the vehicle pose. The study unveils the limitations of single-feature based classification and makes clear that fusion of classifiers is highly beneficial for vehicle verification.

Analysis of the role of the Spitzenkörper in fungal morphogenesis by computer simulation of apical branching in Aspergillus niger

High-resolution video microscopy, image analysis, and computer simulation were used to study the role of the Spitzenkörper (Spk) in apical branching of ramosa-1, a temperature-sensitive mutant of Aspergillus niger. A shift to the restrictive temperature led to a cytoplasmic contraction that destabilized the Spk, causing its disappearance. After a short transition period, new Spk appeared where the two incipient apical branches emerged. Changes in cell shape, growth rate, and Spk position were recorded and transferred to the fungus simulator program to test the hypothesis that the Spk functions as a vesicle supply center (VSC). The simulation faithfully duplicated the elongation of the main hypha and the two apical branches. Elongating hyphae exhibited the growth pattern described by the hyphoid equation. During the transition phase, when no Spk was visible, the growth pattern was nonhyphoid, with consecutive periods of isometric and asymmetric expansion; the apex became enlarged and blunt before the apical branches emerged. Video microscopy images suggested that the branch Spk were formed anew by gradual condensation of vesicle clouds. Simulation exercises where the VSC was split into two new VSCs failed to produce realistic shapes, thus supporting the notion that the branch Spk did not originate by division of the original Spk. The best computer simulation of apical branching morphogenesis included simulations of the ontogeny of branch Spk via condensation of vesicle clouds. This study supports the hypothesis that the Spk plays a major role in hyphal morphogenesis by operating as a VSC—i.e., by regulating the traffic of wall-building vesicles in the manner predicted by the hyphoid model.

Quantitative analysis of senile plaques in Alzheimer disease: observation of log-normal size distribution and molecular epidemiology of differences associated with apolipoprotein E genotype and trisomy 21 (Down syndrome).

The discovery that the epsilon 4 allele of the apolipoprotein E (apoE) gene is a putative risk factor for Alzheimer disease (AD) in the general population has highlighted the role of genetic influences in this extremely common and disabling illness. It has long been recognized that another genetic abnormality, trisomy 21 (Down syndrome), is associated with early and severe development of AD neuropathological lesions. It remains a challenge, however, to understand how these facts relate to the pathological changes in the brains of AD patients. We used computerized image analysis to examine the size distribution of one of the characteristic neuropathological lesions in AD, deposits of A beta peptide in senile plaques (SPs). Surprisingly, we find that a log-normal distribution fits the SP size distribution quite well, motivating a porous model of SP morphogenesis. We then analyzed SP size distribution curves in genotypically defined subgroups of AD patients. The data demonstrate that both apoE epsilon 4/AD and trisomy 21/AD lead to increased amyloid deposition, but by apparently different mechanisms. The size distribution curve is shifted toward larger plaques in trisomy 21/AD, probably reflecting increased A beta production. In apoE epsilon 4/AD, the size distribution is unchanged but the number of SP is increased compared to apoE epsilon 3, suggesting increased probability of SP initiation. These results demonstrate that subgroups of AD patients defined on the basis of molecular characteristics have quantitatively different neuropathological phenotypes.

Proteome analysis of extracellular proteins regulated by the las and rhl quorum sensing systems in Pseudomonas aeruginosa PAO1

The las and rhl quorum sensing (QS) systems regulate the expression of several genes in response to cell density changes in Pseudomonas aeruginosa. Many of these genes encode surface-associated or secreted virulence factors. Proteins from stationary phase culture supernatants were collected from wild-type and P. aeruginosa PAO1 mutants deficient in one or more of the lasRI, rhIRI and vfr genes and analysed using two-dimensional gel electrophoresis. All mutants released significantly lower amounts of protein than the wild-type. Protein spot patterns from each strain were compared using image analysis and visible spot differences were identified using mass spectrometry. Several previously unknown OS-regulated proteins were characterized, including an aminopeptidase (PA2939), an endoproteinase (PrpL) and a unique 'hypothetical' protein (PA0572), which could not be detected in the culture supernatants of Delta/as mutants, although they were unaffected in Deltarhl mutants. Chitin-binding protein (CbpD) and a hypothetical protein (PA4944) with similarity to host factor I (HF-1) could not be detected when any of the lasRI or rhIRI genes were disrupted. Fourteen proteins were present at significantly greater levels in the culture supernatants of OS mutants, suggesting that QS may also negatively control the expression of some genes. Increased levels of two-partner secretion exoproteins (PA0041 and PA4625) were observed and may be linked to increased stability of their cognate transporters in a CS-defective background. Known QS-regulated extracellular proteins, including elastase (lasB), LasA protease (lasA) and alkaline metalloproteinase (aprA) were also detected.

Training Bayesian networks for image segmentation

We are concerned with the problem of image segmentation in which each pixel is assigned to one of a predefined finite number of classes. In Bayesian image analysis, this requires fusing together local predictions for the class labels with a prior model of segmentations. Markov Random Fields (MRFs) have been used to incorporate some of this prior knowledge, but this not entirely satisfactory as inference in MRFs is NP-hard. The multiscale quadtree model of Bouman and Shapiro (1994) is an attractive alternative, as this is a tree-structured belief network in which inference can be carried out in linear time (Pearl 1988). It is an hierarchical model where the bottom-level nodes are pixels, and higher levels correspond to downsampled versions of the image. The conditional-probability tables (CPTs) in the belief network encode the knowledge of how the levels interact. In this paper we discuss two methods of learning the CPTs given training data, using (a) maximum likelihood and the EM algorithm and (b) emphconditional maximum likelihood (CML). Segmentations obtained using networks trained by CML show a statistically-significant improvement in performance on synthetic images. We also demonstrate the methods on a real-world outdoor-scene segmentation task.

Objective analysis of toric intraocular lens rotation and centration

PURPOSE: To assess the repeatability of an objective image analysis technique to determine intraocular lens (IOL) rotation and centration. SETTING: Six ophthalmology clinics across Europe. METHODS: One-hundred seven patients implanted with Akreos AO aspheric IOLs with orientation marks were imaged. Image quality was rated by a masked observer. The axis of rotation was determined from a line bisecting the IOL orientation marks. This was normalized for rotation of the eye between visits using the axis bisecting 2 consistent conjunctival vessels or iris features. The center of ovals overlaid to circumscribe the IOL optic edge and the pupil or limbus were compared to determine IOL centration. Intrasession repeatability was assessed in 40 eyes and the variability of repeated analysis examined. RESULTS: Intrasession rotational stability of the IOL was ±0.79 degrees (SD) and centration was ±0.10 mm horizontally and ±0.10 mm vertically. Repeated analysis variability of the same image was ±0.70 degrees for rotation and ±0.20 mm horizontally and ±0.31 mm vertically for centration. Eye rotation (absolute) between visits was 2.23 ± 1.84 degrees (10%>5 degrees rotation) using one set of consistent conjunctival vessels or iris features and 2.03 ± 1.66 degrees (7%>5 degrees rotation) using the average of 2 sets (P =.13). Poorer image quality resulted in larger apparent absolute IOL rotation (r =-0.45,P<.001). CONCLUSIONS: Objective analysis of digital retroillumination images allows sensitive assessment of IOL rotation and centration stability. Eye rotation between images can lead to significant errors if not taken into account. Image quality is important to analysis accuracy.

Analysis of population dispersion in histological sections

Stereology and other image analysis methods have enabled rapid and objective quantitative measurements to be made on histological sections. These mesurements may include total volumes, surfaces, lengths and numbers of cells and blood vessels or pathological lesions. Histological features, however, may not be randomly distributed across a section but exhibit 'dispersion', a departure from randomness either towards regularity or aggregation. Information of population dispersion may be valuable not only in understanding the two-or three-dimensional structure but also in elucidating the pathogenesis of lesions in pathological conditions. This article reviews some of the statistical methods available for studying dispersion. These range from simple tests of whether the distribution of a histological faeture departs significantly from random to more complex methods which can detect the intensity of aggregation and the sizes, distribution and spacing of the clusters.

A quantitative analysis of optic nerve axons in elderly control subjects and patients with Alzheimer's disease

Objective: To study the density and cross-sectional area of axons in the optic nerve in elderly control subjects and in cases of Alzheimer's disease (AD) using an image analysis system. Methods: Sections of optic nerves from control and AD patients were stained with toluidine blue to reveal axon profiles. Results: The density of axons was reduced in both the center and peripheral portions of the optic nerve in AD compared with control patients. Analysis of axons with different cross-sectional areas suggested a specific loss of the smaller sized axons in AD, i.e., those with areas less that 1.99 μm2. An analysis of axons >11 μm2 in cross-sectional area suggested no specific loss of the larger axons in this group of patients. Conclusions: The data suggest that image analysis provides an accurate and reproducible method of quantifying axons in the optic nerve. In addition, the data suggest that axons are lost throughout the optic nerve with a specific loss of the smaller-sized axons. Loss of the smaller axons may explain the deficits in color vision observed in a significant proportion of patients with AD.