Femke Danckaers

Chronic exposure to haloperidol and olanzapine leads to common and divergent shape changes in the rat hippocampus in the absence of grey-matter volume loss

Background One of the most consistently reported brain abnormalities in schizophrenia (SCZ) is decreased volume and shape deformation of the hippocampus. However, the potential contribution of chronic antipsychotic medication exposure to these phenomena remains unclear. Method We examined the effect of chronic exposure (8 weeks) to clinically relevant doses of either haloperidol (HAL) or olanzapine (OLZ) on adult rat hippocampal volume and shape using ex vivo structural MRI with the brain retained inside the cranium to prevent distortions due to dissection, followed by tensor-based morphometry (TBM) and elastic surface-based shape deformation analysis. The volume of the hippocampus was also measured post-mortem from brain tissue sections in each group. Results Chronic exposure to either HAL or OLZ had no effect on the volume of the hippocampus, even at exploratory thresholds, which was confirmed post-mortem. In contrast, shape deformation analysis revealed that chronic HAL and OLZ exposure lead to both common and divergent shape deformations (q = 0.05, FDR-corrected) in the rat hippocampus. In particular, in the dorsal hippocampus, HAL exposure led to inward shape deformation, whereas OLZ exposure led to outward shape deformation. Interestingly, outward shape deformations that were common to both drugs occurred in the ventral hippocampus. These effects remained significant after controlling for hippocampal volume suggesting true shape changes. Conclusions Chronic exposure to either HAL or OLZ leads to both common and divergent effects on rat hippocampal shape in the absence of volume change. The implications of these findings for the clinic are discussed.

Correspondence Preserving Elastic Surface Registration with Shape Model Prior

In this paper, we describe a framework for surface registration. The framework consists of a combination of rigid registration, elasticity modulated registration and the use of a shape model prior. The main goal in this paper is to minimize the geometric surface registration error while maintaining correspondences. Experiments show improved geometric fit, correspondence, and timing compared to the current state of the art. Possible applications of the framework are construction of correspondences for shape models, reconstruction of missing parts, and artifact reduction.

Building a Statistical Shape Model of the Apple from Corresponded Surfaces

In this paper, a method for building a 3D statistical shape model of the apple is described. The framework consists of two parts. First, a reference surface is registered to each apple surface, derived from 3D CT scans of apples, of the population to obtain meaningful correspondences between the shapes. In the second part, the corresponded surfaces are used to build a statistical shape model from the population of apples. This model maps out the variability within the population and by adapting the shape model parameters, new, realistic surfaces can be obtained. By parameterizing the surface, an apple can be described with a compact set of basis functions, which has applications in surface fitting description, recognition, or meshing, e.g. for storage simulation. The constructed apple shape model is tested on performance and has proven to be a good representation of the population and can be used in many applications.

Full Body Statistical Shape Modeling with Posture Normalization

Realistic virtual mannequins, that represent body shapes that occur in the target population, are valuable tools for product developers who design near-body products. Statistical shape modeling is a promising approach to map out the variability of body shapes. The strength of statistical shape models (SSM) is their ability to capture most of the shape variation with only a few shape modes. Unfortunately, the shape variation captured by SSMs of human bodies is often polluted by variations in posture, which substantially reduces the compactness of those models. In this paper, we propose a fast and data driven framework to build a posture invariant SSM. The normalized SSM is shown to be substantially more compact than the non-normalized SSM. Using five shape modes, the normalized SSM is 23% more compact than the non-normalized SSM.

Evaluation of 3D Body Shape Predictions Based on Features

The human body comes in many sizes and shapes. For design purposes, it is useful to be able to quickly simulate a virtual mannequin of a customer. A statistical shape model can be used for this purpose, because it describes the main variations of body shape inside the model’s population. From this model, the specific features of each person in the population are known. Therefore, a mapping between the shape model parameters and specific features can be calculated, which allows adjusting the body shape, in an intuitive way. In this work, we have investigated how accurate a body shape can be predicted based on a set of features and which features are most suitable for this purpose. Height, weight, and hip circumference appeared to be the most suitable features to accurately predict the body shape.

Three-dimensional quantitative analysis of healthy foot shape: a proof of concept study

BackgroundFoot morphology has received increasing attention from both biomechanics researches and footwear manufacturers. Usually, the morphology of the foot is quantified by 2D footprints. However, footprint quantification ignores the foot’s vertical dimension and hence, does not allow accurate quantification of complex 3D foot shape.MethodsThe shape variation of healthy 3D feet in a population of 31 adult women and 31 adult men who live in Belgium was studied using geometric morphometric methods. The effect of different factors such as sex, age, shoe size, frequency of sport activity, Body Mass Index (BMI), foot asymmetry, and foot loading on foot shape was investigated. Correlation between these factors and foot shape was examined using multivariate linear regression.ResultsThe complex nature of a foot’s 3D shape leads to high variability in healthy populations. After normalizing for scale, the major axes of variation in foot morphology are (in order of decreasing variance): arch height, combined ball width and inter-toe distance, global foot width, hallux bone orientation (valgus-varus), foot type (e.g. Egyptian, Greek), and midfoot width. These first six modes of variation capture 92.59% of the total shape variation. Higher BMI results in increased ankle width, Achilles tendon width, heel width and a thicker forefoot along the dorsoplantar axis. Age was found to be associated with heel width, Achilles tendon width, toe height and hallux orientation. A bigger shoe size was found to be associated with a narrow Achilles tendon, a hallux varus, a narrow heel, heel expansion along the posterior direction, and a lower arch compared to smaller shoe size. Sex was found to be associated with differences in ankle width, Achilles tendon width, and heel width. Frequency of sport activity was associated with Achilles tendon width and toe height.ConclusionA detailed analysis of the 3D foot shape, allowed by geometric morphometrics, provides insights in foot variations in three dimensions that can not be obtained from 2D footprints. These insights could be applied in various scientific disciplines, including orthotics and shoe design.

A Combined Statistical Shape Model of the Scalp and Skull of the Human Head

In this paper, we describe a framework to build a combined statistical shape model (SSM) of the outer surface of the scalp and the inner and outer surface of the skull of the human head. Such an SSM is a valuable tool when designing headgear, as it captures the variability of head geometry of a given population, enabling detailed analysis of the relation between the shape of the scalp and the skull. A combined SSM of the head may allow to work towards population based Finite Element (FE) models e.g. for safety and comfort predictions when wearing headgear. Therefore, a correspondence between the skull and scalp surfaces, originating from MRI scans, is determined using elastic surface registration. The combined SSM shown to be compact, to be able to generalize to unseen instances by adjusting the shape parameters and to be shape specific. Therefore, we can assure that, by adjusting the shape parameters, a broad range of realistic head shapes can be formed.

Building 3D Statistical Shape Models of Horticultural Products

A method to build a 3D statistical shape model of horticultural products is described. The framework consists of two parts. First, the surfaces of the horticultural products, which are extracted from X-ray CT scans, are registered to obtain meaningful correspondences between the surfaces. In the second part, a statistical shape model is built from these corresponded surfaces, which maps out the variability of the surfaces and allows to generate new, realistic surfaces. The proposed shape modelling method is applied to 30 Jonagold apples, 30 bell peppers, and 52 zucchini. The average geometric registration error between the original instance and the deformed reference instance is 0.015 ± 0.011 mm for the apple dataset, 0.106 ± 0.026 mm for the bell pepper dataset, and 0.027 ± 0.007 mm for the Zucchini dataset. All shape models are shown to be an excellent representation of their specific population, as they are compact and able to generalize to an unseen sample of the population.

Foot abnormality mapping using statistical shape modelling

About 20% of the population suffer from disabling foot or ankle pain that require the use of foot orthotics. Traditionally, those foot orthotics are designed manually, but digital procedures are desired to provide a faster, more objective, and more reliable workflow. In this study, we introduce a method for detecting shape abnormalities in feet for the purposes of pathology diagnosis and orthotic design. The proposed method consists of two phases. In the training phase, a statistical 3D foot model (based on 42 healthy subjects) is built. In the test phase, the landmarks of a new 3D foot scan are compared to the trained model. A landmark is detected as an outlier if it is in the extreme ranges. This testing process is repeated at all landmarks to identify all abnormal foot regions. Preliminary results show that, when testing a foot of a known pathology (hallux valgus, heel spur, foot pronation), we are able to detect abnormal regions accurately. We also examined the effect of using rigid or similarity-based alignment during 3D model building and abnormality detection. We show that our proposed method is a faster and a more objective approach than traditional approaches for abnormality detection of the foot. As such, this method may prove useful in the medical diagnosis of foot pathologies and in automated orthotic design.

An Articulating Statistical Shape Model of the Human Hand

This paper presents a registration framework for the construction of a statistical shape model of the human hand in a standard pose. It brings a skeletonized reference model of an individual human hand into correspondence with optical 3D surface scans of hands by sequentially applying articulation-based registration and elastic surface registration. Registered surfaces are then fed into a statistical shape modelling algorithm based on principal component analysis. The model-building technique has been evaluated on a dataset of optical scans from 100 healthy individuals, acquired with a 3dMD scanning system. It is shown that our registration framework provides accurate geometric and anatomical alignment, and that the shape basis of the resulting statistical model provides a compact representation of the specific population. The model also provides insight into the anatomical variation of the lower arm and hand, which is useful information for the design of well-fitting products.