Biomedical subjects

Dirk Vandermeulen

Publications and source records attributed to Dirk Vandermeulen.

15 recordsLinked to original sources

PubMed2006

Craniofacial reconstruction using a combined statistical model of face shape and soft tissue depths: methodology and validation.

Forensic facial reconstruction aims at estimating the facial outlook associated with an unidentified skull specimen. Estimation is generally based on tabulated average values of soft tissue thicknesses measured at a sparse set of landmarks on the skull. Traditional 'plastic' methods apply modeling clay or plasticine on a cast of the skull, approximating the estimated tissue depths at the landmarks and interpolating in between. Current computerized techniques mimic this landmark interpolation procedure using a single static facial surface template. However, the resulting reconstruction is biased by the specific choice of the template and no face-specific regularization is used during the interpolation process. We reduce the template bias by using a flexible statistical model of a dense set of facial surface points, combined with an associated sparse set of skull-based landmarks. This statistical model is constructed from a facial database of (N = 118) individuals and limits the reconstructions to statistically plausible outlooks. The actual reconstruction is obtained by fitting the skull-based landmarks of the template model to the corresponding landmarks indicated on a digital copy of the skull to be reconstructed. The fitting process changes the face-specific statistical model parameters in a regularized way and interpolates the remaining landmark fit error using a minimal bending thin-plate spline (TPS)-based deformation. Furthermore, estimated properties of the skull specimen (BMI, age and gender, e.g.) can be incorporated as conditions on the reconstruction by removing property-related shape variation from the statistical model description before the fitting process. The proposed statistical method is validated, both in terms of accuracy and identification success rate, based on leave-one-out cross-validation tests applied on the facial database. Accuracy results are obtained by statistically analyzing the local 3D facial surface differences of the reconstructions and their corresponding ground truth. Identification success rate is obtained by comparing, based on correlation, Euclidean distance matrix (EDM) signatures of the reconstructed and the original 3D facial surfaces in the database. A subjective identification success rate is quantified based on face-pool tests. Finally a qualitative comparison is made between facial reconstructions of a real-case skull, based on two typical static face models and our statistical model, showing the shortcomings of current face models and the improved performance of the statistical model.

Adolescent↗

PubMed2006

Computerized craniofacial reconstruction using CT-derived implicit surface representations.

In forensic craniofacial reconstruction, facial features of an unknown individual are estimated from an unidentified skull, based on a mixture of experimentally obtained guidelines on the relationship between soft tissues and the underlying skeleton. In this paper, we investigate the possibility of using full 3D cross-sectional CT images for establishing a reference database of densely sampled distances between the external surfaces of the skull and head for automated craniofacial reconstruction. For each CT image in the reference database, the hard tissue (skull) and soft tissue (head) volumes are automatically segmented and transformed into signed distance transform (sDT) images, representing for each voxel in this image the Euclidean distance to the closest point on the skull and head surface, respectively, distances being positive (negative) for voxels inside (outside) the skull/head. Multiple craniofacial reconstructions are obtained by first warping each reference skull sDT maps to the target skull sDT using a B-spline based free form deformation algorithm and subsequently applying these warps to the reference head sDT maps. A single reconstruction of the target head surface is defined as the zero level set of the arithmetic average of all warped reference head sDT maps, but other reconstructions are possible, biasing the result to subject specific attributes (age, BMI, gender). Both qualitative and quantitative tests (measuring the similarity between the 3D reconstructed and corresponding original head surface) on a small (N = 20) database are presented to proof the validity of the concept.

Databases as Topic↗

PubMed2006

An information theoretic approach for non-rigid image registration using voxel class probabilities.

We propose two information theoretic similarity measures that allow to incorporate tissue class information in non-rigid image registration. The first measure assumes that tissue class probabilities have been assigned to each of the images to be registered by prior segmentation of both of them. One image is then non-rigidly deformed to match the other such that the fuzzy overlap of corresponding voxel object labels becomes similar to the ideal case whereby the tissue probability maps of both images are identical. Image similarity is assessed during registration by the divergence between the ideal and actual joint class probability distributions of both images. A second registration measure is proposed that applies in case a segmentation is available for only one of the images, for instance an atlas image that is to be matched to a study image to guide the segmentation thereof. Intensities in one image are matched to the fuzzy class labels in the other image by minimizing the conditional entropy of the intensities in the first image given the class labels in the second image. We derive analytic expressions for the gradient of each measure with respect to individual voxel displacements to derive a force field that drives the registration process, which is regularized by a viscous fluid model. The performance of the class-based measures is evaluated in the context of non-rigid inter-subject registration and atlas-based segmentation of MR brain images and compared with maximization of mutual information using only intensity information. Our results demonstrate that incorporation of class information in the registration measure significantly improves the overlap between corresponding tissue classes after non-rigid matching. The methods proposed here open new perspectives for integrating segmentation and registration in a single process, whereby the output of one is used to guide the other.

Algorithms↗

PubMed2005

Feature-based statistical analysis of structural MR data for automatic detection of focal cortical dysplastic lesions.

This paper presents a method for fully automated detection and localization of Focal Cortical Dysplastic (FCD) lesions from anatomical magnetic resonance (MR) images of the human brain. Model-based tissue classification of the image under study was applied first such that a gray matter (GM) segmentation map is obtained of which we demonstrate that it also includes possible FCD lesions. Cortical thickness was estimated at each voxel using an appropriate distance transform applied to the binarized GM object and an FCD specific feature map was constructed by computing the ratio of cortical thickness over absolute image intensity gradient at each voxel. In absence of any prior anatomical hypothesis on the spatial location of the lesion, a statistical parameter map was constructed by evaluating the evidence for each gray matter voxel against the null hypothesis of no difference in the feature map of the patient versus similar maps obtained for a group of normal controls. Voxel clusters for which the null hypothesis was found to be improbable at optimally selected thresholds for cluster height and extent were reported as lesions. The method was applied to a surgical series of 17 FCD patient images that were compared against a group of 64 neurologically normal controls. The method correctly detected and located the FCD lesion in 9 out of 17 FCD cases (53%) using a threshold that minimized false positives and 12 of 17 (71%) using a threshold that allowed more false positive results. The detected lesions had a median volume of 7.2 cm(3) versus 2.9 cm(3) for the non-detected lesions. The detected lesions more often had an increased cortical thickness on T1 than the non-detected lesions (P=0.015, Fisher's exact test). Due to a high variance of the feature maps in the temporal lobes and insula, detection of FCD lesions in these regions appeared more difficult than in other brain regions with lower variance.

Adolescent↗

PubMed2005

Automatic analysis of cerebral asymmetry: an exploratory study of the relationship between brain torque and planum temporale asymmetry.

Leftward occipital and rightward frontal lobe asymmetry (brain torque) and leftward planum temporale asymmetry have been consistently reported in postmortem and in vivo neuroimaging studies of the human brain. Here automatic image analysis techniques are applied to quantify global and local asymmetries, and investigate the relationship between brain torque and planum temporale asymmetries on T1-weighted magnetic resonance (MR) images of 30 right-handed young healthy subjects (15 male, 15 female). Previously described automatic cerebral hemisphere extraction and 3D interhemispheric reflection-based methods for studying brain asymmetry are applied with a new technique, LowD (Low Dimension), which enables automatic quantification of brain torque. LowD integrates extracted left and right cerebral hemispheres in columns orthogonal to the midsagittal plane (2D column maps), and subsequently integrates slices along the brain's anterior-posterior axis (1D slice profiles). A torque index defined as the magnitude of occipital and frontal lobe asymmetry is computed allowing exploratory investigation of relationships between this global asymmetry and local asymmetries found in the planum temporale. LowD detected significant torque in the 30 subjects with occipital and frontal components found to be highly correlated (P<0.02). Significant leftward planum temporale asymmetry was detected (P<0.05), and the torque index correlated with planum temporale asymmetry (P<0.001). However, torque and total brain volume were not correlated. Therefore, although components of cerebral asymmetry may be related, their magnitude is not influenced by total hemisphere volume. LowD provides increased sensitivity for detection and quantification of brain torque on an individual subject basis, and future studies will apply these techniques to investigate the relationship between cerebral asymmetry and functional laterality.

Adult↗

PubMed2005

Plaque and stent artifact reduction in subtraction CT angiography using nonrigid registration and a volume penalty.

Computed tomography angiography (CTA) is an established tool for vessel imaging. Yet, high-intense structures in the contrast image can seriously hamper luminal visualisation. This can be solved by subtraction CTA, where a native image is subtracted from the contrast image. However, patient and organ motion limit the application of this technique. Within this paper, a fully automated intensity-based nonrigid 3D registration algorithm for subtraction CT angiography is presented, using a penalty term to avoid volume change during registration. Visual and automated validation on four clinical datasets clearly show that the algorithm strongly reduces motion artifacts in subtraction CTA. With our method, 39% to 99% of the artifacts disappear, also those caused by minimal displacement of stents or calcified plaques. This results in a better visualisation of the vessel lumen, also of the smaller vessels, allowing a faster and more accurate inspection of the whole vascular structure, especially in case of stenosis.

Algorithms↗

PubMed2005

[Computer-assisted facial reconstruction: recent developments and trends].

Three-dimensional (3D) craniofacial reconstruction can be a useful tool in the identification of an unknown body. The progress in computer science and the improvement of medical imaging technologies during recent years has had a significant impact on this domain. New facial soft tissue depth data have been obtained. New guidelines for facial feature properties such as nose projection, eye protrusion or mouth width, have been suggested, but also older theories and "rules of thumbs" have been critically evaluated based on digital technology. New fast, flexible and objective 3D reconstruction computer-based programs are in full development. Employing the newer technologies and permanently evaluating the obtained results will hopefully lead to more accurate reconstructions.

Algorithms↗

PubMed2005

Semi-automated ultrasound facial soft tissue depth registration: method and validation.

A mobile and fast, semi-automatic ultrasound (US) system was developed for facial soft tissue depth registration. The system consists of an A-Scan ultrasound device connected to a portable PC with interfacing and controlling software. For 52 cephalometric landmarks, the system was tested for repeatability and accuracy by evaluating intra-observer agreement and comparing ultrasound and CT-scan results on 12 subjects planned for craniofacial surgery, respectively. A paired t-test evaluating repeatability of the ultrasound measurements showed 5.7% (n = 3) of the landmarks being significantly different (p < 0.01). US and CT-scan results showed significant differences (p < 0.01) using a Wilcoxon signed rank test analysis for 11.5% (n = 6) of the landmarks. This is attributed to a difference in the volunteer's head position between lying (CT) and sitting (US). Based on these tests, we conclude that the proposed registration system and measurement protocol allows relatively fast (52 landmarks/20 min), non-invasive, repeatable and accurate acquisition of facial soft tissue depth measurements.

Adult↗

PubMed2003

Application of a new image analysis technique to study brain asymmetry in schizophrenia.

The hypothesis that normal brain torque (i.e. rightward frontal and leftward occipital asymmetry) is anomalous in schizophrenia (Crow, 1997. Trends in Neuroscience, 20, 339-343) was tested by application of a novel image analysis technique on three-dimensional magnetic resonance images obtained in 26 adult patients with chronic schizophrenia (18 males, 8 females) and 24 controls (14 males, 10 females). Right and left cerebral hemisphere tissue was extracted via non-linear co-registration with a mask image, and maps were computed of inter-hemispheric differences in tissue volume in an array of columns of voxels orthogonal to the mid-plane (2D), and profiles of coronal slice volumes (1D). Furthermore, integration of two-dimensional column maps gave approximate lobar asymmetries, and occipital and frontal asymmetries were combined to give a volumetric measure of brain torque. Significant brain torque was revealed in male and female control and patient groups, and did not correlate with brain size. Frontal and occipital asymmetries were significantly correlated in all groups. Both frontal and occipital components of torque were significantly increased in males than females. Patients tended to have reduced torque, particularly the leftward occipital component. Furthermore, 3/26 patients (but no controls) had reversed torque (leftward frontal and rightward occipital asymmetry). Contrary to Crow's hypothesis, brain torque was not significantly reduced in patients with schizophrenia relative to controls, although reversal of torque was found in three cases. Future studies with larger sample sizes should consider sexual dimorphism and specific symptoms in relation to asymmetry.

Brain↗

PubMed2003

Non-rigid image registration using a statistical spline deformation model.

We propose a statistical spline deformation model (SSDM) as a method to solve non-rigid image registration. Within this model, the deformation is expressed using a statistically trained B-spline deformation mesh. The model is trained by principal component analysis of a training set. This approach allows to reduce the number of degrees of freedom needed for non-rigid registration by only retaining the most significant modes of variation observed in the training set. User-defined transformation components, like affine modes, are merged with the principal components into a unified framework. Optimization proceeds along the transformation components rather then along the individual spline coefficients. The concept of SSDM's is applied to the temporal registration of thorax CR-images using pattern intensity as the registration measure. Our results show that, using 30 training pairs, a reduction of 33% is possible in the number of degrees of freedom without deterioration of the result. The same accuracy as without SSDM's is still achieved after a reduction up to 66% of the degrees of freedom.

Algorithms↗

PubMed2003

Accuracy of diffusion-weighted MR imaging in the diagnosis of sporadic Creutzfeldt-Jakob disease.

The definitive diagnosis of sporadic Creutzfeldt-Jakob disease (sCJD) is based on brain autopsy. The 14-3-3 analysis in the CSF is considered a highly sensitive and specific procedure. Sensitivity, specificity and accuracy of EEG, the 14-3-3 assay and MR imaging in 12 patients referred for suspected sCJD were calculated. We suggest that diffusion-weighted MR imaging (DWI) should be included in the array of diagnostic tests because of the 100 % sensitivity and specificity.

Aged↗

PubMed2003

A viscous fluid model for multimodal non-rigid image registration using mutual information.

We propose a multimodal free-form registration algorithm based on maximization of mutual information. The warped image is modeled as a viscous fluid that deforms under the influence of forces derived from the gradient of the mutual information registration criterion. Parzen windowing is used to estimate the joint intensity probability of the images to be matched. The method is evaluated for non-rigid inter-subject registration of MR brain images. The accuracy of the method is verified using simulated multi-modal MR images with known ground truth deformation. The results show that the root mean square difference between the recovered and the ground truth deformation is smaller than 1 voxel. We illustrate the application of the method for atlas-based brain tissue segmentation in MR images in case of gross morphological differences between atlas and patient images.

Algorithms↗

PubMed2003

A unifying framework for partial volume segmentation of brain MR images.

Accurate brain tissue segmentation by intensity-based voxel classification of magnetic resonance (MR) images is complicated by partial volume (PV) voxels that contain a mixture of two or more tissue types. In this paper, we present a statistical framework for PV segmentation that encompasses and extends existing techniques. We start from a commonly used parametric statistical image model in which each voxel belongs to one single tissue type, and introduce an additional downsampling step that causes partial voluming along the borders between tissues. An expectation-maximization approach is used to simultaneously estimate the parameters of the resulting model and perform a PV classification. We present results on well-chosen simulated images and on real MR images of the brain, and demonstrate that the use of appropriate spatial prior knowledge not only improves the classifications, but is often indispensable for robust parameter estimation as well. We conclude that general robust PV segmentation of MR brain images requires statistical models that describe the spatial distribution of brain tissues more accurately than currently available models.

Algorithms↗

PubMed2002

Evaluation of image features and search strategies for segmentation of bone structures in radiographs using Active Shape Models.

In this paper, we evaluate various image features and different search strategies for fitting Active Shape Models (ASM) to bone object boundaries in digitized radiographs. The original ASM method iteratively refines the pose and shape parameters of the point distribution model driving the ASM by a least squares fit of the shape to update the target points at the estimated object boundary position, as determined by a suitable object boundary criterion. We propose an improved search procedure that is more robust against outlier configurations in the boundary target points by requiring subsequent shape changes to be smooth, which is imposed by a smoothness constraint on the displacement of neighbouring target points at each iteration and implemented by a minimal cost path approach. We compare the original ASM search method and our improved search algorithm with a third method that does not rely on iteratively refined target point positions, but instead optimizes a global Bayesian objective function derived from statistical a priori contour shape and image models. Extensive validation of these methods on a database containing more than 400 images of the femur, humerus and calcaneus using the manual expert segmentation as ground truth shows that our minimal cost path method is the most robust. We also evaluate various measures for capturing local image appearance around each boundary point and conclude that the Mahalanobis distance applied to normalized image intensity profiles extracted normal to the shape is the most suitable criterion among the tested ones for guiding the ASM optimization.

Algorithms↗

PubMed2002

Retrospective correction of the heel effect in hand radiographs.

A method for the retrospective correction of intensity inhomogeneities induced by the heel effect in digital radiographs is presented. The method is based on a mathematical model for the heel effect derived from the acquisition geometry. The model parameters are estimated by fitting the model to the image intensity data in the background or direct exposure area only where the heel effect is directly measurable, while the correction is then applied to the whole image. The method iterates between background segmentation and heel effect correction until convergence. We illustrate the performance of the method on flat field and phantom images and demonstrate its robustness on a database of 137 diagnostic hand radiographs.

Algorithms↗