Biomedical subjects

Paul Suetens

Publications and source records attributed to Paul Suetens.

At least 19 recordsLinked to original sources

PubMed2006

Assessment of bone segmentation quality of cone-beam CT versus multislice spiral CT: a pilot study.

OBJECTIVES: The objective of this study was to quantitatively assess the quality of jawbone models generated from cone beam computed tomography (CBCT) by comparison with similar models obtained from multislice spiral computed tomography (MSCT). MATERIAL AND METHODS: Three case studies were performed involving images of anthropomorphic head phantoms and real patients acquired with 3 CBCT (NewTom 9000 DVT, Accuitomo 3D, and i-CAT) and 2 MSCT scanners (Somatom VolumeZoom and Lightspeed). Bone was segmented from the CBCT and MSCT images using global thresholding. CBCT vs MSCT segmentation differences were assessed by comparing bone thickness measurements at anatomically corresponding sites, identified automatically by CBCT to MSCT image registration. RESULTS: There was a statistically significant difference between the MSCT and CBCT segmented bone thicknesses, varying from 0.05 +/- 0.47 mm (i-CAT) up to 1.2 +/- 1.00 mm (3D Accuitomo, posterior maxilla). CONCLUSIONS: An automated, reproducible, and observer-independent method has been developed to assess the quality of CBCT bone models using MSCT as a clinically established method of reference. Our validation method is generally applicable in cases where no geometric ground-truth is available.

Algorithms↗

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

State-of-the-art on cone beam CT imaging for preoperative planning of implant placement.

Orofacial diagnostic imaging has grown dramatically in recent years. As the use of endosseous implants has revolutionized oral rehabilitation, a specialized technique has become available for the preoperative planning of oral implant placement: cone beam computed tomography (CT). This imaging technology provides 3D and cross-sectional views of the jaws. It is obvious that this hardware is not in the same class as CT machines in cost, size, weight, complexity, and radiation dose. It is thus considered to be the examination of choice when making a risk-benefit assessment. The present review deals with imaging modalities available for preoperative planning purposes with a specific focus on the use of the cone beam CT and software for planning of oral implant surgery. It is apparent that cone beam CT is the medium of the future, thus, many changes will be performed to improve these. Any adaptation of the future systems should go hand in hand with a further dose optimalization.

Anatomy, Cross-Sectional↗

PubMed2006

Computer-aided detection of colonic polyps using low-dose CT acquisitions.

RATIONALE AND OBJECTIVES: This report proposes an alternative method for the automatic detection of colonic polyps that is robust enough to be directly applicable on low-dose computed tomographic data. MATERIALS AND METHODS: The polyp modeling process takes into account both the gray-level appearance of polyps (intensity profiles) and their geometry (extended Gaussian images). Spherical harmonic decompositions are used for comparison purposes, allowing fast estimation of the similarity between a candidate and a set of previously computed models. Starting from the original raw data (acquired at 55 mA), five patient data sets (prone and supine scans) are reconstructed at different dose levels (to 5 mA) by using different kernel filters, slice overlaps, and increments. Additionally, the efficacy of applying an edge-preserving smoothing filter before detection is assessed. RESULTS: Although image quality decreases when decreasing acquisition milliamperes, all polyps greater than 6 mm are detected successfully, even at 15 mA. Although not important at high doses, smoothing improves detection results for ultra-low-dose (tube current<15 mA) data. CONCLUSION: The advantage of low-dose scans is a significant decrease in effective dose from 4.93 to 1.61 mSv while retaining high detection values, particularly important when thinking of population screening.

Algorithms↗

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

Computer aided detection for low-dose CT colonography.

The paper describes a method for automatic detection of colonic polyps, robust enough to be directly applied to low-dose CT colonographic datasets. Polyps are modeled using gray level intensity profiles and extended Gaussian images. Spherical harmonic decompositions ensure an easy comparison between a polyp candidate and a set of polypoid models, found in a previously built database. The detection sensitivity and specificity values are evaluated at different dose levels. Starting from the original raw-data (acquired at 55mAs), 5 patient datasets (prone and supine scans) are reconstructed at different dose levels (down to 5mAs), using different kernel filters and slice increments. Although the image quality decreases when lowering the acquisition mAs, all polyps above 6mm are successfully detected even at 15 mAs. Accordingly the effective dose can be reduced from 4.93mSv to 1.61 mSv, without affecting detection capabilities, particularly important when thinking of population screening.

Algorithms↗

PubMed2005

Robust visualization of the dental occlusion by a double scan procedure.

A detailed visualization of the dental occlusion in 3D image-based planning environments for oral and maxillofacial planning is important. With CT imaging however, this occlusion is often deteriorated by streak artifacts caused by amalgam fillings. Moreover, more detailed surface information at the level of the dental cuspids is often desired. In this paper, a double scan technique is introduced to image the dental occlusion by means of a newly designed 3D splint. The patient wears this splint between the upper and lower teeth during CT-scan. In a second step, the splint is positioned between the plaster casts of the upper and lower jaw, and this setup is scanned. Based on markers in the 3D splint, both data sets are fused and a combined visualization is possible. The accuracy, robustness and applicability in clinical routine is shown. This technology enables meticulous 3D cephalometric analysis, detailed maxillofacial planning and opens possibilities towards intraoperative support.

Cadaver↗

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

Optimization of geometrical calibration in pinhole SPECT.

Previously, we developed a method to determine the acquisition geometry of a pinhole camera. This information is needed for the correct reconstruction of pinhole single photon emission computed tomography images. The method uses a calibration phantom consisting of three point sources and their positions in the field of view (FOV) influence the accuracy of the geometry estimate. This paper proposes two particular configurations of point sources with specific positions and orientations in the FOV for optimal image reconstruction accuracy. For the proposed calibration setups, inaccuracies of the geometry estimate due to noise in the calibration data, only cause subresolution inaccuracies in reconstructed images. The calibration method also uses a model of the point source configuration, which is only known with limited accuracy. The study demonstrates, however, that, with the proposed calibration setups, the error in reconstructed images is comparable to the error in the phantom model.

Algorithms↗

PubMed2005

An augmented reality system for patient-specific guidance of cardiac catheter ablation procedures.

We present a system to assist in the treatment of cardiac arrhythmias by catheter ablation. A patient-specific three-dimensional (3-D) anatomical model, constructed from magnetic resonance images, is merged with fluoroscopic images in an augmented reality environment that enables the transfer of electrocardiography (ECG) measurements and cardiac activation times onto the model. Accurate mapping is realized through the combination of: a new calibration technique, adapted to catheter guided treatments; a visual matching registration technique, allowing the electrophysiologist to align the model with contrast-enhanced images; and the use of virtual catheters, which enable the annotation of multiple ECG measurements on the model. These annotations can be visualized by color coding on the patient model. We provide an accuracy analysis of each of these components independently. Based on simulation and experiments, we determined a segmentation error of 0.6 mm, a calibration error in the order of 1 mm and a target registration error of 1.04 +/- 0.45 mm. The system provides a 3-D visualization of the cardiac activation pattern which may facilitate and improve diagnosis and treatment of the arrhytmia. Because of its low cost and similar advantages we believe our approach can compete with existing commercial solutions, which rely on dedicated hardware and costly catheters. We provide qualitative results of the first clinical use of the system in 11 ablation procedures.

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↗

PubMed2004

Evaluation of anatomy based reconstruction for partial volume correction in brain FDG-PET.

UNLABELLED: FDG-PET contributes to the diagnosis and management of neurological diseases. In some of these diseases, pathological gray matter (GM) areas may have a reduced FDG uptake. Detection of these regions can be difficult and some remain undiscovered using visual assessment. The main reason for this detection problem is the relatively small thickness of GM compared to the spatial resolution of PET, known as the partial volume effect. We have developed an anatomy-based maximum-a-posteriori reconstruction algorithm (A-MAP) which corrects for this effect during the reconstruction using segmented magnetic resonance (MR) data. Monte-Carlo based 3-D brain software phantom simulations were used to investigate the influence of the strength of anatomy-based smoothing in GM, the influence of misaligned MR data, and the effect of local segmentation errors. A human observer study was designed to assess the detection performance of A-MAP versus post-smoothed maximum-likelihood (ML) reconstruction. We demonstrated the applicability of A-MAP using real patient data. The results for A-MAP showed improved recovery values and robustness for local segmentation errors. Misaligned MR data reduced the recovery values towards those obtained by post-smoothed ML, for small registration errors. In the human observer study, detection accuracy of hypometabolic regions was significantly improved using A-MAP, compared to post-smoothed ML (P < 0.004). The patient study confirmed the applicability of A-MAP in clinical practice. CONCLUSION: A-MAP is a promising technique for voxel-based partial volume correction of FDG-PET of the human brain.

Adult↗

PubMed2004

Anatomical-based FDG-PET reconstruction for the detection of hypo-metabolic regions in epilepsy.

Positron emission tomography (PET) of the cerebral glucose metabolism has shown to be useful in the presurgical evaluation of patients with epilepsy. Between seizures, PET images using fluorodeoxyglucose (FDG) show a decreased glucose metabolism in areas of the gray matter (GM) tissue that are associated with the epileptogenic region. However, detection of subtle hypo-metabolic regions is limited by noise in the projection data and the relatively small thickness of the GM tissue compared to the spatial resolution of the PET system. Therefore, we present an iterative maximum-a-posteriori based reconstruction algorithm, dedicated to the detection of hypo-metabolic regions in FDG-PET images of the brain of epilepsy patients. Anatomical information, derived from magnetic resonance imaging data, and pathophysiological knowledge was included in the reconstruction algorithm. Two Monte Carlo based brain software phantom experiments were used to examine the performance of the algorithm. In the first experiment, we used perfect, and in the second, imperfect anatomical knowledge during the reconstruction process. In both experiments, we measured signal-to-noise ratio (SNR), root mean squared (rms) bias and rms standard deviation. For both experiments, bias was reduced at matched noise levels, when compared to post-smoothed maximum-likelihood expectation-maximization (ML-EM) and maximum a posteriori reconstruction without anatomical priors. The SNR was similar to that of ML-EM with optimal post-smoothing, although the parameters of the prior distributions were not optimized. We can conclude that the use of anatomical information combined with prior information about the underlying pathology is very promising for the detection of subtle hypo-metabolic regions in the brain of patients with epilepsy.

Algorithms↗

PubMed2004

RF-based two-dimensional cardiac strain estimation: a validation study in a tissue-mimicking phantom.

Strain and strain rate imaging have been shown to be useful techniques for the assessment of cardiac function. However, one of the major problems of these techniques is their angle dependency. In order to overcome this problem, a new method for estimating the strain (rate) tensor had previously been proposed by our lab. The aim of this study was to validate this methodology in a phantom setup. A tubular thick-walled tissue-mimicking phantom was fixed in a water tank. Varying the intraluminal pressure resulted in a cyclic radial deformation. The 2D strain was calculated from the 2D velocity estimates, obtained from 2D radio frequency (RF) tracking using a 1D kernel. Additionally, ultrasonic microcrystals were implanted on the outer and inner walls of the tube in order to give an independent measurement of the instantaneous wall thickness. The two methods were compared by means of linear regression, the correlation coefficient, and Bland-Altman statistics. As expected, the strain estimates dominated by the azimuth velocity component were less accurate than the ones dominated by the axial velocity component. Correlation coefficients were found to be r = 0.78 for the former estimates and r = 0.83 was found for the latter. Given that the overall shape and timing of the 2D deformation were very accurate (r = 0.95 and r = 0.84), these results were within acceptable limits for clinical applications. The 2D RF-tracking using a 1D kernel thus allows for 2D, and therefore angle-independent, strain estimation.

Algorithms↗

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↗