Landmark detection in 2D bioimages for geometric morphometrics: a multi-resolution tree-based approach

The detection of anatomical landmarks in bioimages is a necessary but tedious step for geometric morphometrics studies in many research domains. We propose variants of a multi-resolution tree-based approach to speed-up the detection of landmarks in bioimages. We extensively evaluate our method variants on three different datasets (cephalometric, zebrafish, and drosophila images). We identify the key method parameters (notably the multi-resolution) and report results with respect to human ground truths and existing methods. Our method achieves recognition performances competitive with current existing approaches while being generic and fast. The algorithms are integrated in the open-source Cytomine software and we provide parameter configuration guidelines so that they can be easily exploited by end-users. Finally, datasets are readily available through a Cytomine server to foster future research

New quantitative approaches reveal the spatial preference of nuclear compartments in mammalian fibroblasts

The nuclei of higher eukaryotic cells display compartmentalization and certain nuclear compartments have been shown to follow a degree of spatial organization. To date, the study of nuclear organization has often involved simple quantitative procedures that struggle with both the irregularity of the nuclear boundary and the problem of handling replicate images. Such studies typically focus on inter-object distance, rather than spatial location within the nucleus. The concern of this paper is the spatial preference of nuclear compartments, for which we have developed statistical tools to quantitatively study and explore nuclear organization. These tools combine replicate images to generate ‘aggregate maps' which represent the spatial preferences of nuclear compartments. We present two examples of different compartments in mammalian fibroblasts (WI-38 and MRC-5) that demonstrate new knowledge of spatial preference within the cell nucleus. Specifically, the spatial preference of RNA polymerase II is preserved across normal and immortalized cells, whereas PML nuclear bodies exhibit a change in spatial preference from avoiding the centre in normal cells to exhibiting a preference for the centre in immortalized cells. In addition, we show that SC35 splicing speckles are excluded from the nuclear boundary and localize throughout the nucleoplasm and in the interchromatin space in non-transformed WI-38 cells. This new methodology is thus able to reveal the effect of large-scale perturbation on spatial architecture and preferences that would not be obvious from single cell imaging

Anisotropic Radial Layout for Visualizing Centrality and Structure in Graphs

This paper presents a novel method for layout of undirected graphs, where nodes (vertices) are constrained to lie on a set of nested, simple, closed curves. Such a layout is useful to simultaneously display the structural centrality and vertex distance information for graphs in many domains, including social networks. Closed curves are a more general constraint than the previously proposed circles, and afford our method more flexibility to preserve vertex relationships compared to existing radial layout methods. The proposed approach modifies the multidimensional scaling (MDS) stress to include the estimation of a vertex depth or centrality field as well as a term that penalizes discord between structural centrality of vertices and their alignment with this carefully estimated field. We also propose a visualization strategy for the proposed layout and demonstrate its effectiveness using three social network datasets.Comment: Appears in the Proceedings of the 25th International Symposium on Graph Drawing and Network Visualization (GD 2017

The effects of immediate vision on implicit hand maps

Perceiving the external spatial location of the limbs using position sense requires that immediate proprioceptive afferent signals be combined with a stored body model specifying the size and shape of the body. Longo and Haggard (Proc Natl Acad Sci USA 107:11727–11732, 2010) developed a method to isolate and measure this body model in the case of the hand in which participants judge the perceived location in external space of several landmarks on their occluded hand. The spatial layout of judgments of different landmarks is used to construct implicit hand maps, which can then be compared with actual hand shape. Studies using this paradigm have revealed that the body model of the hand is massively distorted, in a highly stereotyped way across individuals, with large underestimation of finger length and overestimation of hand width. Previous studies using this paradigm have allowed participants to see the locations of their judgments on the occluding board. Several previous studies have demonstrated that immediate vision, even when wholly non-informative, can alter processing of somatosensory signals and alter the reference frame in which they are localised. The present study therefore investigated whether immediate vision contributes to the distortions of implicit hand maps described previously. Participants judged the external spatial location of the tips and knuckles of their occluded left hand either while being able to see where they were pointing (as in previous studies) or while blindfolded. The characteristic distortions of implicit hand maps reported previously were clearly apparent in both conditions, demonstrating that the distortions are not an artefact of immediate vision. However, there were significant differences in the magnitude of distortions in the two conditions, suggesting that vision may modulate representations of body size and shape, even when entirely non-informative

On the origin of spaces: morphometric foundations of urban form evolution

The modern discipline of urban morphology gives us a ground for the comparative analysis of cities, which increasingly includes specific quantitative elements. In this paper, we make a further step forward towards the definition of a general method for the classification of urban form. We draw from morphometrics and taxonomy in life sciences to propose such method, which we name ‘urban morphometrics’. We then test it on a unit of the urban landscape named ‘Sanctuary Area’ (SA), explored in 45 cities whose origins span four historic time periods: Historic (medieval), Industrial (19th century), New Towns (post-WWII, high-rise) and Sprawl (post-WWII, low-rise). We describe each SA through 207 physical dimensions and then use these to discover features that discriminate them among the four temporal groups. Nine dimensions emerge as sufficient to correctly classify 90% of the urban settings by their historic origins. These nine attributes largely identify an area's ‘visible identity’ as reflected by three characteristics: (1) block perimeterness, or the way buildings define the street-edge; (2) building coverage, or the way buildings cover the land and (3) regular plot coverage, or the extent to which blocks are made of plots that have main access from a street. Hierarchical cluster analysis utilising only the nine key variables nearly perfectly clusters each SA according to its historic origin; moreover, the resulting dendrogram shows, just after WWII, the first ‘bifurcation’ of urban history, with the emergence of the modern city as a new ‘species’ of urban form. With ‘urban morphometrics’ we hope to extend urban morphological research and contribute to understanding the way cities evolve

Comparison of geometric morphometric outline methods in the discrimination of age-related differences in feather shape

BACKGROUND: Geometric morphometric methods of capturing information about curves or outlines of organismal structures may be used in conjunction with canonical variates analysis (CVA) to assign specimens to groups or populations based on their shapes. This methodological paper examines approaches to optimizing the classification of specimens based on their outlines. This study examines the performance of four approaches to the mathematical representation of outlines and two different approaches to curve measurement as applied to a collection of feather outlines. A new approach to the dimension reduction necessary to carry out a CVA on this type of outline data with modest sample sizes is also presented, and its performance is compared to two other approaches to dimension reduction. RESULTS: Two semi-landmark-based methods, bending energy alignment and perpendicular projection, are shown to produce roughly equal rates of classification, as do elliptical Fourier methods and the extended eigenshape method of outline measurement. Rates of classification were not highly dependent on the number of points used to represent a curve or the manner in which those points were acquired. The new approach to dimensionality reduction, which utilizes a variable number of principal component (PC) axes, produced higher cross-validation assignment rates than either the standard approach of using a fixed number of PC axes or a partial least squares method. CONCLUSION: Classification of specimens based on feather shape was not highly dependent of the details of the method used to capture shape information. The choice of dimensionality reduction approach was more of a factor, and the cross validation rate of assignment may be optimized using the variable number of PC axes method presented herein

Persistent homology to analyse 3D faces and assess body weight gain

In this paper, we analyse patterns in face shape variation due to weight gain. We propose the use of persistent homology descriptors to get geometric and topological information about the configuration of anthropometric 3D face landmarks. In this way, evaluating face changes boils down to comparing the descriptors computed on 3D face scans taken at different times. By applying dimensionality reduction techniques to the dissimilarity matrix of descriptors, we get a space in which each face is a point and face shape variations are encoded as trajectories in that space. Our results show that persistent homology is able to identify features which are well related to overweight and may help assessing individual weight trends. The research was carried out in the context of the European project SEMEOTICONS, which developed a multisensory platform which detects and monitors over time facial signs of cardio-metabolic risk

Landmarking the brain for geometric morphometric analysis: An error study

Neuroanatomic phenotypes are often assessed using volumetric analysis. Although powerful and versatile, this approach is limited in that it is unable to quantify changes in shape, to describe how regions are interrelated, or to determine whether changes in size are global or local. Statistical shape analysis using coordinate data from biologically relevant landmarks is the preferred method for testing these aspects of phenotype. To date, approximately fifty landmarks have been used to study brain shape. Of the studies that have used landmark-based statistical shape analysis of the brain, most have not published protocols for landmark identification or the results of reliability studies on these landmarks. The primary aims of this study were two-fold: (1) to collaboratively develop detailed data collection protocols for a set of brain landmarks, and (2) to complete an intra- and inter-observer validation study of the set of landmarks. Detailed protocols were developed for 29 cortical and subcortical landmarks using a sample of 10 boys aged 12 years old. Average intra-observer error for the final set of landmarks was 1.9 mm with a range of 0.72 mm-5.6 mm. Average inter-observer error was 1.1 mm with a range of 0.40 mm-3.4 mm. This study successfully establishes landmark protocols with a minimal level of error that can be used by other researchers in the assessment of neuroanatomic phenotypes. © 2014 Chollet et al