Image-based vs. mesh-based statistical appearance models of the human femur: Implications for finite element simulations.

Statistical appearance models have recently been introduced in bone mechanics to investigate bone geometry and mechanical properties in population studies. The establishment of accurate anatomical correspondences is a critical aspect for the construction of reliable models. Depending on the representation of a bone as an image or a mesh, correspondences are detected using image registration or mesh morphing. The objective of this study was to compare image-based and mesh-based statistical appearance models of the femur for finite element (FE) simulations. To this aim, (i) we compared correspondence detection methods on bone surface and in bone volume; (ii) we created an image-based and a mesh-based statistical appearance models from 130 images, which we validated using compactness, representation and generalization, and we analyzed the FE results on 50 recreated bones vs. original bones; (iii) we created 1000 new instances, and we compared the quality of the FE meshes. Results showed that the image-based approach was more accurate in volume correspondence detection and quality of FE meshes, whereas the mesh-based approach was more accurate for surface correspondence detection and model compactness. Based on our results, we recommend the use of image-based statistical appearance models for FE simulations of the femur.

Personalized X-Ray Reconstruction of the Proximal Femur via Intensity-Based Non-rigid 2D-3D Registration

This paper presents a new approach for reconstructing a patient-specific shape model and internal relative intensity distribution of the proximal femur from a limited number (e.g., 2) of calibrated C-arm images or X-ray radiographs. Our approach uses independent shape and appearance models that are learned from a set of training data to encode the a priori information about the proximal femur. An intensity-based non-rigid 2D-3D registration algorithm is then proposed to deformably fit the learned models to the input images. The fitting is conducted iteratively by minimizing the dissimilarity between the input images and the associated digitally reconstructed radiographs of the learned models together with regularization terms encoding the strain energy of the forward deformation and the smoothness of the inverse deformation. Comprehensive experiments conducted on images of cadaveric femurs and on clinical datasets demonstrate the efficacy of the present approach.

Statistical shape analysis via principal factor analysis

Statistical shape analysis techniques commonly employed in the medical imaging community, such as active shape models or active appearance models, rely on principal component analysis (PCA) to decompose shape variability into a reduced set of interpretable components. In this paper we propose principal factor analysis (PFA) as an alternative and complementary tool to PCA providing a decomposition into modes of variation that can be more easily interpretable, while still being a linear efficient technique that performs dimensionality reduction (as opposed to independent component analysis, ICA). The key difference between PFA and PCA is that PFA models covariance between variables, rather than the total variance in the data. The added value of PFA is illustrated on 2D landmark data of corpora callosa outlines. Then, a study of the 3D shape variability of the human left femur is performed. Finally, we report results on vector-valued 3D deformation fields resulting from non-rigid registration of ventricles in MRI of the brain.

3D documentation and visualization of external injury findings by integration of simple photography in CT/MRI data sets (IprojeCT).

This study evaluated the feasibility of documenting patterned injury using three dimensions and true colour photography without complex 3D surface documentation methods. This method is based on a generated 3D surface model using radiologic slice images (CT) while the colour information is derived from photographs taken with commercially available cameras. The external patterned injuries were documented in 16 cases using digital photography as well as highly precise photogrammetry-supported 3D structured light scanning. The internal findings of these deceased were recorded using CT and MRI. For registration of the internal with the external data, two different types of radiographic markers were used and compared. The 3D surface model generated from CT slice images was linked with the photographs, and thereby digital true-colour 3D models of the patterned injuries could be created (Image projection onto CT/IprojeCT). In addition, these external models were merged with the models of the somatic interior. We demonstrated that 3D documentation and visualization of external injury findings by integration of digital photography in CT/MRI data sets is suitable for the 3D documentation of individual patterned injuries to a body. Nevertheless, this documentation method is not a substitution for photogrammetry and surface scanning, especially when the entire bodily surface is to be recorded in three dimensions including all external findings, and when precise data is required for comparing highly detailed injury features with the injury-inflicting tool.

Mesh-based vs. Image-based Statistical Appearance Model of the Human Femur: a Preliminary Comparison Study for the Creation of Finite Element Meshes

Statistical models have been recently introduced in computational orthopaedics to investigate the bone mechanical properties across several populations. A fundamental aspect for the construction of statistical models concerns the establishment of accurate anatomical correspondences among the objects of the training dataset. Various methods have been proposed to solve this problem such as mesh morphing or image registration algorithms. The objective of this study is to compare a mesh-based and an image-based statistical appearance model approaches for the creation of nite element(FE) meshes. A computer tomography (CT) dataset of 157 human left femurs was used for the comparison. For each approach, 30 finite element meshes were generated with the models. The quality of the obtained FE meshes was evaluated in terms of volume, size and shape of the elements. Results showed that the quality of the meshes obtained with the image-based approach was higher than the quality of the mesh-based approach. Future studies are required to evaluate the impact of this finding on the final mechanical simulations.

Genetics of male nuptial colour divergence between sympatric sister species of a Lake Victoria cichlid fish

The hypothesis of sympatric speciation by sexual selection has been contentious. Several recent theoretical models of sympatric speciation by disruptive sexual selection were tailored to apply to African cichlids. Most of this work concludes that the genetic architecture of female preference and male trait is a key determinant of the likelihood of disruptive sexual selection to result in speciation. We investigated the genetic architecture controlling male nuptial colouration in a sympatric sibling species pair of cichlid fish from Lake Victoria, which differ conspicuously in male colouration and female mating preferences for these. We estimated that the difference between the species in male nuptial red colouration is controlled by a minimum number of two to four genes with significant epistasis and dominance effects. Yellow colouration appears to be controlled by one gene with complete dominance. The two colours appear to be epistatically linked. Knowledge on how male colouration segregates in hybrid generations and on the number of genes controlling differences between species can help us assess whether assumptions made in simulation models of sympatric speciation by sexual selection are realistic. In the particular case of the two sister species that we studied a small number of genes causing major differences in male colouration may have facilitated the divergence in male colouration associated with speciation.

Assortative mating among Lake Malawi cichlid fish populations is not simply predictable from male nuptial colour

Background: Research on the evolution of reproductive isolation in African cichlid fishes has largely focussed on the role of male colours and female mate choice. Here, we tested predictions from the hypothesis that allopatric divergence in male colour is associated with corresponding divergence in preference. Methods: We studied four populations of the Lake Malawi Pseudotropheus zebra complex. We predicted that more distantly-related populations that independently evolved similar colours would interbreed freely while more closely-related populations with different colours mate assortatively. We used microsatellite genotypes or mesh false-floors to assign paternity. Fisher's exact tests as well as Binomial and Wilcoxon tests were used to detect if mating departed from random expectations. Results: Surprisingly, laboratory mate choice experiments revealed significant assortative mating not only between population pairs with differently coloured males, but between population pairs with similarly-coloured males too. This suggested that assortative mating could be based on nonvisual cues, so we further examined the sensory basis of assortative mating between two populations with different male colour. Conducting trials under monochromatic (orange) light, intended to mask the distinctive male dorsal fin hues (blue v orange) of these populations, did not significantly affect the assortative mating by female P. emmiltos observed under control conditions. By contrast, assortative mating broke down when direct contact between female and male was prevented. Conclusion: We suggest that non-visual cues, such as olfactory signals, may play an important role in mate choice and behavioural isolation in these and perhaps other African cichlid fish. Future speciation models aimed at explaining African cichlid radiations may therefore consider incorporating such mating cues in mate choice scenarios.

Climate-induced interannual variability of marine primary and export production in three global coupled climate carbon cycle models

Fully coupled climate carbon cycle models are sophisticated tools that are used to predict future climate change and its impact on the land and ocean carbon cycles. These models should be able to adequately represent natural variability, requiring model validation by observations. The present study focuses on the ocean carbon cycle component, in particular the spatial and temporal variability in net primary productivity (PP) and export production (EP) of particulate organic carbon (POC). Results from three coupled climate carbon cycle models (IPSL, MPIM, NCAR) are compared with observation-based estimates derived from satellite measurements of ocean colour and results from inverse modelling (data assimilation). Satellite observations of ocean colour have shown that temporal variability of PP on the global scale is largely dominated by the permanently stratified, low-latitude ocean (Behrenfeld et al., 2006) with stronger stratification (higher sea surface temperature; SST) being associated with negative PP anomalies. Results from all three coupled models confirm the role of the low-latitude, permanently stratified ocean for anomalies in globally integrated PP, but only one model (IPSL) also reproduces the inverse relationship between stratification (SST) and PP. An adequate representation of iron and macronutrient co-limitation of phytoplankton growth in the tropical ocean has shown to be the crucial mechanism determining the capability of the models to reproduce observed interactions between climate and PP.

Psychophysiological evidence for the genuineness of swimming-style colour synaesthesia

Recently, swimming-style colour synaesthesia was introduced as a new form of synaesthesia. A synaesthetic Stroop test was used to establish its genuineness. Since Stroop interference can occur for any type of overlearned association, in the present study we used a modified Stroop test and psychophysiological synaesthetic conditioning to further establish the genuineness of this form of synaesthesia. We compared the performance of a swimming-style colour synaesthete and a control who was trained on swimming-style colour associations. Our results showed that behavioural aspects of swimming-style colour synaesthesia can be mimicked in a trained control. Importantly, however, our results showed a psychophysiological conditioning effect for the synaesthete only. We discuss the theoretical relevance of swimming-style colour synaesthesia according to different models of synaesthesia. We conclude that swimming-style colour synaesthesia is a genuine form of synaesthesia, can be mimicked behaviourally in non-synaesthetes, and is best explained by a re-entrant feedback model.

Enhanced associative memory for colour (but not shape or location) in synaesthesia

People with grapheme-colour synaesthesia have been shown to have enhanced memory on a range of tasks using both stimuli that induce synaesthesia (e.g. words) and, more surprisingly, stimuli that do not (e.g. certain abstract visual stimuli). This study examines the latter by using multi-featured stimuli consisting of shape, colour and location conjunctions (e.g. shape A + colour A + location A; shape B + colour B + location B) presented in a recognition memory paradigm. This enables distractor items to be created in which one of these features is ‘unbound’ with respect to the others (e.g. shape A + colour B + location A; shape A + colour A + location C). Synaesthetes had higher recognition rates suggesting an enhanced ability to bind certain visual features together into memory. Importantly, synaesthetes’ false alarm rates were lower only when colour was the unbound feature, not shape or location. We suggest that synaesthetes are “colour experts” and that enhanced perception can lead to enhanced memory in very specific ways; but, not for instance, an enhanced ability to form associations per se. The results support contemporary models that propose a continuum between perception and memory.

Diagnosing synaesthesia with online colour pickers: Maximising sensitivity and specificity

The most commonly used method for formally assessing grapheme-colour synaesthesia (i.e., experiencing colours in response to letter and/or number stimuli) involves selecting colours from a large colour palette on several occasions and measuring consistency of the colours selected. However, the ability to diagnose synaesthesia using this method depends on several factors that have not been directly contrasted. These include the type of colour space used (e.g., RGB, HSV, CIELUV, CIELAB) and different measures of consistency (e.g., city block and Euclidean distance in colour space). This study aims to find the most reliable way of diagnosing grapheme-colour synaesthesia based on maximising sensitivity (i.e., ability of a test to identify true synaesthetes) and specificity (i.e., ability of a test to identify true non-synaesthetes). We show, applying ROC (Receiver Operating Characteristics) to binary classification of a large sample of self-declared synaesthetes and non-synaesthetes, that the consistency criterion (i.e., cut-off value) for diagnosing synaesthesia is considerably higher than the current standard in the field. We also show that methods based on perceptual CIELUV and CIELAB colour models (rather than RGB and HSV colour representations) and Euclidean distances offer an even greater sensitivity and specificity than most currently used measures. Together, these findings offer improved heuristics for the behavioural assessment of grapheme-colour synaesthesia.