Frans M Vos

University of Amsterdam, Amsterdam, North Holland, Netherlands

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Publications (125)126.93 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: PURPOSE To prospectively compare conventional MRI, dynamic contrast-enhanced (DCE-)MRI and diffusion weighted imaging (DWI) sequences to histopathology of surgical specimens in Crohn’s disease (CD). METHOD AND MATERIALS 3T MR enterography was performed in 25 consecutive CD patients scheduled for surgery within 4 weeks. A total of one to four sections per patient were chosen for detailed image analysis. Evaluated features including mural thickness, T1 signal ratio and T2 signal ratio and on DCE-MRI maximum enhancement (ME), initial slope of increase (ISI) and time to peak (TTP) and on DWI apparent diffusion coefficient (ADC), were compared to location matched-histopathologic grading of acute inflammation score (AIS) and fibrostenosis score (FS) by Spearman correlation, Kruskal Wallis and Mann-Whitney test. RESULTS Twenty patients (mean age 38 years, range 21-73, 12 females) were included and 50 bowel locations (35 terminal ileum, 11 ascending colon, 2 transverse colon, 2 descending colon) were matched to AIS and FS. Median AIS was 3 and median FS 1. Mural thickness, T1 signal ratio, T2 signal ratio, ME and ISI correlated significantly to AIS (r = 0.634, 0.392, 0.485, 0.526, 0.514, respectively; all p<0.05). Mural thickness, T1 and T2 signal ratio differed significantly between the grades of FS (p<0.001, p=0.001, p=0.021, respectively). ME, ISI and ADC values differed significantly between the non-fibrotic sections and the fibrotic sections (p<0.001, p=0.001, p=0.023, respectively). CONCLUSION Quantitative parameters from conventional, DCE-MRI and DWI sequences correlate significantly to histopathologic scores of surgical specimens. DCE-MRI and DWI give comparable results but do not outperform conventional MRI parameters. CLINICAL RELEVANCE/APPLICATION DCE- and DWI-MRI can be used for quantitative evaluation of Crohn's disease activity.
    Radiological Society of North America 2013 Scientific Assembly and Annual Meeting; 12/2013
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    ABSTRACT: OBJECTIVE. The purpose of this article is to assess the interobserver variability for scoring MRI features of Crohn disease activity and to correlate two MRI scoring systems to the Crohn disease endoscopic index of severity (CDEIS). MATERIALS AND METHODS. Thirty-three consecutive patients with Crohn disease undergoing 3-T MRI examinations (T1-weighted with IV contrast medium administration and T2-weighted sequences) and ileocolonoscopy within 1 month were independently evaluated by four readers. Seventeen MRI features were recorded in 143 bowel segments and were used to calculate the MR index of activity and the Crohn disease MRI index (CDMI) score. Multirater analysis was performed for all features and scoring systems using intraclass correlation coefficient (icc) and kappa statistic. Scoring systems were compared with ileocolonoscopy with CDEIS using Spearman rank correlation. RESULTS. Thirty patients (median age, 32 years; 21 women and nine men) were included. MRI features showed fair-to-good interobserver variability (intraclass correlation coefficient or kappa varied from 0.30 to 0.69). Wall thickness in millimeters, presence of edema, enhancement pattern, and length of the disease in each segment showed a good interobserver variability between all readers (icc = 0.69, κ = 0.66, κ = 0.62, and κ = 0.62, respectively). The MR index of activity and CDMI scores showed good reproducibility (icc = 0.74 and icc = 0.78, respectively) and moderate CDEIS correlation (r = 0.51 and r = 0.59, respectively). CONCLUSION. The reproducibility of individual MRI features overall is fair to good, with good reproducibility for the most commonly used features. When combined into the MR index of activity and CDMI score, overall reproducibility is good. Both scores show moderate agreement with CDEIS.
    American Journal of Roentgenology 12/2013; 201(6):1220-1228. · 2.90 Impact Factor
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    ABSTRACT: We propose an information processing pipeline for segmenting parts of the bowel in abdominal magnetic resonance (MR) images that are affected with Crohn's disease (CD). Given a MRI test volume, it is first oversegmented into supervoxels and each supervoxel is analyzed to detect presence of Crohn's disease using random forest (RF) classifiers. The supervoxels identified as containing diseased tissues define the volume of interest (VOI). All voxels within the VOI are further investigated to segment the diseased region. Probability maps are generated for each voxel using a second set of RF classifiers which give the probabilities of each voxel being diseased, normal or background. The negative log-likelihood of these maps are used as penalty costs in a graph cut segmentation framework. Low level features like intensity statistics, texture anisotropy and curvature asymmetry, and high level context features are used at different stages. Smoothness constraints are imposed based on semantic information (importance of each feature to the classification task) derived from the second set of learned RF classifiers. Experimental results show that our method achieves high segmentation accuracy with Dice metric values of 0.90±0.04 and Hausdorff distance of 7.3±0.8 mm. Semantic information and context features are an integral part of our method and are robust to different levels of added noise.
    IEEE transactions on medical imaging. 09/2013;
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    ABSTRACT: To prospectively compare conventional MRI sequences, dynamic contrast enhanced (DCE) MRI and diffusion weighted imaging (DWI) with histopathology of surgical specimens in Crohn's disease. 3-T MR enterography was performed in consecutive Crohn's disease patients scheduled for surgery within 4 weeks. One to four sections of interest per patient were chosen for analysis. Evaluated parameters included mural thickness, T1 ratio, T2 ratio; on DCE-MRI maximum enhancement (ME), initial slope of increase (ISI), time-to-peak (TTP); and on DWI apparent diffusion coefficient (ADC). These were compared with location-matched histopathological grading of inflammation (AIS) and fibrosis (FS) using Spearman correlation, Kruskal-Wallis and Chi-squared tests. Twenty patients (mean age 38 years, 12 female) were included and 50 sections (35 terminal ileum, 11 ascending colon, 2 transverse colon, 2 descending colon) were matched to AIS and FS. Mural thickness, T1 ratio, T2 ratio, ME and ISI correlated significantly with AIS, with moderate correlation (r = 0.634, 0.392, 0.485, 0.509, 0.525, respectively; all P < 0.05). Mural thickness, T1 ratio, T2 ratio, ME, ISI and ADC correlated significantly with FS (all P < 0.05). Quantitative parameters from conventional, DCE-MRI and DWI sequences correlate with histopathological scores of surgical specimens. DCE-MRI and DWI parameters provide additional information. • Conventional MR enterography can be used to assess Crohn's disease activity. • Several MRI parameters correlate with inflammation and fibrosis scores from histopathology. • Dynamic contrast enhanced imaging and diffusion weighted imaging give additional information. • Quantitative MRI parameters can be used as biomarkers to evaluate Crohn's disease activity.
    European Radiology 09/2013; · 4.34 Impact Factor
  • Zhang Li, Lucas J. van Vliet, Frans M. Vos
    Abdominal Imaging. Computational and Clinical Applications; 09/2013
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    ABSTRACT: CT colonography (CTC) is one of the recommended methods for colorectal cancer screening. The subject's preparation is one of the most burdensome aspects of CTC with a cathartic bowel preparation. Tagging of the bowel content with an oral contrast medium facilitates CTC with limited bowel preparation. Unfortunately, such preparations adversely affect the 3D image quality. Thus far, data acquired after very limited bowel preparation were evaluated with a 2D reading strategy only. Existing cleansing algorithms do not work sufficiently well to allow a primary 3D reading strategy. We developed an electronic cleansing algorithm, aimed to realize optimal 3D image quality for low-dose CTC with 24-hour limited bowel preparation. The method employs a principal curvature flow algorithm to remove heterogeneities within poorly tagged fecal residue. In addition, a pattern recognition based approach is used to prevent polyp-like protrusions on the colon surface from being removed by the method. Two experts independently evaluated 40 CT colonography cases by means of a primary 2D approach without involvement of electronic cleansing as well as by a primary 3D method after electronic cleansing. The data contained four variations of 24-hour limited bowel preparation and was based on a low radiation dose scanning protocol. The sensitivity for lesions 6mm was significantly higher for the primary 3D reading strategy (84%) than for the primary 2D reading strategy (68%) (p = 0.031). The reading time was increased from 5:39min (2D) to 7:09min (3D) (p = 0.005); the readers' confidence was reduced from 2.3 (2D) to 2.1 (3D) (p = 0.013) on a 3-point Likert scale. Polyp conspicuity for cleansed submerged lesions was similar to not submerged lesions (p = 0.06). To our knowledge this study is the first to describe and clinically validate an electronic cleansing algorithm that facilitates low-dose CTC with 24-hour limited bowel preparation.
    IEEE transactions on bio-medical engineering 05/2013; · 2.15 Impact Factor
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    ABSTRACT: Anatomical alignment in neuroimaging studies is of such importance that considerable effort is put into improving the registration used to establish spatial correspondence. Tract-based spatial statistics (TBSS) is a popular method for comparing diffusion characteristics across subjects. TBSS establishes spatial correspondence using a combination of nonlinear registration and a "skeleton projection" that may break topological consistency of the transformed brain images. We therefore investigated feasibility of replacing the two-stage registration-projection procedure in TBSS with a single, regularized, high-dimensional registration. To optimize registration parameters and to evaluate registration performance in diffusion MRI, we designed an evaluation framework that uses native space probabilistic tractography for 23 white matter tracts, and quantifies tract similarity across subjects in standard space. We optimized parameters for two registration algorithms on two diffusion datasets of different quality. We investigated reproducibility of the evaluation framework, and of the optimized registration algorithms. Next, we compared registration performance of the regularized registration methods and TBSS. Finally, feasibility and effect of incorporating the improved registration in TBSS were evaluated in an example study. The evaluation framework was highly reproducible for both algorithms (R(2) 0.993; 0.931). The optimal registration parameters depended on the quality of the dataset in a graded and predictable manner. At optimal parameters, both algorithms outperformed the registration of TBSS, showing feasibility of adopting such approaches in TBSS. This was further confirmed in the example experiment.
    NeuroImage 03/2013; · 6.25 Impact Factor
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    ABSTRACT: We propose a graph cut based method to segment regions in abdominal magnetic resonance (MR) images affected with Crohn's disease (CD). Intensity, texture, curvature and context information are used with random forest (RF) classifiers to calculate probability maps for graph cut segmentation. The RF classifiers also provide semantic information used to design a novel smoothness cost. Experimental results on 26 real patient data shows our method accurately segments the diseased areas. Inclusion of semantic information significantly improves segmentation accuracy and its importance is reflected in quantitative measures and visual results.
    Biomedical Imaging (ISBI), 2013 IEEE 10th International Symposium on; 01/2013
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    ABSTRACT: We address the problem of weakly supervised segmentation (WSS) of medical images which is more challenging and has potentially greater applications in the medical imaging community. Training images are labeled only by the classes they contain, and not by the pixel labels. We make use of the Multi Image Model (MIM) for weakly supervised segmentation which exploits superpixel features and assigns labels to every pixel. MIM connects superpixels from all training images in a data driven fashion. Test images are integrated into the MIM for predicting their labels, thus making full use of the training samples. Experimental results on abdominal magnetic resonance (MR) images of patients with Crohn's disease show that WSS performs close to fully supervised methods and given sufficient samples can perform on par with fully supervised methods.
    Biomedical Imaging (ISBI), 2013 IEEE 10th International Symposium on; 01/2013
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    ABSTRACT: The purpose of this study is to gain a better understanding of the changes due to osteoarthritis (OA) occurring in the thumb carpometacarpal (CMC) joint by comparing quantitative geometrical measurements in computed tomography scans of healthy and pathological joints in various stages of OA. The measurements were (1) the subluxation of the metacarpal on the trapezium, (2) distance from the scaphoid centre to the metacarpal base, and (3) distance from the metacarpal base to the articulating surface of the trapezium. The three-dimensional position of three characteristic points on the metacarpal, trapezium, and scaphoid were detected in each of the 90 wrists we scanned. The distances between the points were compared by statistical analysis. With high accuracy, we have been able to confirm and quantify that subluxation occurs in the dorso-radial direction. A significant difference in trapezium height and joint space width was found between the OA and control groups. The results indicate how to restore the centre of rotation in surgical treatment of OA with total joint arthroplasty, but the clinical relevance of these findings has to be tested in further clinical studies.
    The Journal of hand surgery, European volume 11/2012; · 0.04 Impact Factor
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    ABSTRACT: Analyzing Diffusion Tensor Image data of the human brain of large study groups is complex and demands new, sophisticated and computationally intensive pipelines that can efficiently be executed. We present our progress over the past five years in the development and porting of the DTI analysis pipeline to a grid infrastructure. Starting with simple jobs submitted from the command-line, we moved towards a workflow-based implementation and finally into the e-BioInfra Gateway, which offers a web interface for the execution of selected biomedical data analysis software on the Dutch Grid. This gateway is currently being actively used by neuroscientists and for educational purposes.
    Future Generation Computer Systems 10/2012; 28(8):1194–1204. · 2.64 Impact Factor
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    ABSTRACT: We present an extension of the symmetric ICP algorithm that is unbiased for an arbitrary number (N > or = 2) of shapes, using rigid transformations and scaling. The method does not require the selection of a reference shape or registration order and hence it is unbiased towards any of the registered shapes. The functional to be minimized is non-linear in the transformation parameters and thus computationally complex. We therefore propose a first order approximation that estimates the transformation parameters in a closed form, with computational complexity (see text for symbol)(N2). Using a set of wrist bones, we show that the least-squares minimization and the proposed approximation converge to the same solution. Experiments also show that the proposed algorithms lead to smaller registration errors than algorithms that select a reference shape or register to an evolving mean shape. The low computational cost and trivial parallelization enable the alignment of large numbers of bones.
    Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. 01/2012; 15(Pt 2):155-62.
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    ABSTRACT: In this paper a novel groupwise registration algorithm is proposed for the unbiased registration of a large number of densely sampled point clouds. The method fits an evolving mean shape to each of the example point clouds thereby minimizing the total deformation. The registration algorithm alternates between a computationally expensive, but parallelizable, deformation step of the mean shape to each example shape and a very inexpensive step updating the mean shape. The algorithm is evaluated by comparing it to a state of the art registration algorithm. Bone surfaces of wrists, segmented from CT data with a voxel size of 0.3 x 0.3 x 0.3 mm3, serve as an example test set. The negligible bias and registration error of about 0.12 mm for the proposed algorithm are similar to those in. However, current point cloud registration algorithms usually have computational and memory costs that increase quadratically with the number of point clouds, whereas the proposed algorithm has linearly increasing costs, allowing the registration of a much larger number of shapes: 48 versus 8, on the hardware used.
    Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. 01/2012; 15(Pt 3):164-71.
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    ABSTRACT: Magnetic resonance imaging is increasingly used for abdominal evaluation and is more and more considered as the optimal imaging technique for detection of mural inflammation in patients with Crohn's disease. Grading the disease activity is important in daily clinical practice to monitor the medical treatment and is assessed by evaluating different magnetic resonance imaging features. Unfortunately, only moderate interobserver agreement is reported for most of the subjective features and should be improved. A computer-assisted model for automatic detection of abnormalities, ability to grade disease severity, and thereby influence clinical disease management based on magnetic resonance imaging is missing. Recent techniques have focused on semi-automated methods for classification and segmentation of the bowel and also on objective measurement of bowel wall enhancement using absolute T1-values or dynamic contrast-enhanced imaging. This article reviews the available computerized techniques, as well as preferred developments.
    Abdominal Imaging 12/2011; · 1.91 Impact Factor
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    ABSTRACT: Direct imaging of ligament damage in the wrist remains a challenge. Still, such damage can be assessed indirectly through the analysis of changes in wrist pose and motion pattern. For this purpose we built a statistical reference model that describes healthy motion patterns. We show that such a model can also be used to detect and quantify pathologies. A model that only describes the global translations and rotations of the carpal bones is insufficiently accurate due to size and shape variations of the bones. We present a local statistical motion model that minimizes the influence of size and shape differences by analyzing the coordinate differences of pairs of points on adjacent bone surfaces. These differences are determined in a set of 14 healthy example wrists imaged in a range of poses by means of 4D-RX imaging. The distribution of the differences as a function of the pose form the local statistical motion model (LSMM). Translations of 2 mm and rotations of 20° with respect to the healthy example wrists are detected as outliers in the point pair distributions. An evaluation involving wrists with a damaged ligament between scaphoid and lunate shows that not only joint space widenings can be detected, but also shifts of congruent bone surfaces. The LSMM is also used to perform a virtual reconstruction of the most likely healthy wrist after a simulated perturbation of bones. The reconstruction precision is shown to be about 1 mm. Therefore, the presented 4D statistical model of wrist bone movement may become a valuable clinical tool for diagnosis and surgical planning.
    IEEE Transactions on Medical Imaging 10/2011; 31(3):613-25. · 4.03 Impact Factor
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    ABSTRACT: Inflammatory bowel diseases (IBD) constitute one of the largest healthcare problems in the Western World. Grading of the disease severity is important to determine treatment strategy and to quantify the response to treatment. The Time Injection Curves (TICs) after injecting a contrast agent contain important information on the degree of inflammation of the bowel wall. However, respiratory and peristaltic motions complicate an easy analysis of such curves since spatial correspondence over time is lost. We propose a gated, 3D non-rigid motion correction method that robustly extracts time intensity curves from bowel segments in free-breathing abdominal DCE-MRI data. It is shown that the mean TICs in small bowel segments could be robustly computed and contained less fluctuations than prior to the registration.
    Proceedings of the Third international conference on Abdominal Imaging: computational and Clinical Applications; 09/2011
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    ABSTRACT: Monitoring glaucoma patients and ensuring optimal treatment requires accurate and precise detection of progression. Many glaucomatous progression detection strategies may be formulated for Scanning Laser Polarimetry (SLP) data of the local nerve fiber thickness. In this paper, several strategies, all based on repeated GDx VCC SLP measurements, are tested to identify the optimal one for clinical use. The parameters of the methods were adapted to yield a set specificity of 97.5% on real image series. For a fixed sensitivity of 90%, the minimally detectable loss was subsequently determined for both localized and diffuse loss. Due to the large size of the required data set, a previously described simulation method was used for assessing the minimally detectable loss. The optimal strategy was identified and was based on two baseline visits and two follow-up visits, requiring two-out-of-four positive tests. Its associated minimally detectable loss was 5-12 μm, depending on the reproducibility of the measurements.
    Computers in biology and medicine 09/2011; 41(9):857-64. · 1.27 Impact Factor
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    ABSTRACT: Motoneuron disease is a term encompassing three phenotypes defined largely by the balance of upper versus lower motoneuron involvement, namely amyotrophic lateral sclerosis, primary lateral sclerosis and progressive muscular atrophy. However, neuroradiological and pathological findings in these phenotypes suggest that degeneration may exceed the neuronal system upon which clinical diagnosis is based. To further delineate the phenotypes within the motoneuron disease spectrum, this controlled study assessed the upper- and extra-motoneuron white matter involvement in cohorts of patients with motoneuron disease phenotypes shortly after diagnosis by comparing diffusion tensor imaging data of the different cohorts to those of healthy controls and directly between the motoneuron disease phenotypes (n = 12 for each cohort). Furthermore, we acquired follow-up data 6 months later to evaluate fractional anisotropy changes over time. Combined use of diffusion tensor tractography of the corticospinal tract and whole-brain voxel-based analysis allowed for comparison of the sensitivity of these techniques to detect white matter involvement in motoneuron disease. The voxel-based analysis demonstrated varying extents of white matter involvement in different phenotypes of motoneuron disease, albeit in quite similar anatomical locations. In general, fractional anisotropy reductions were modest in progressive muscular atrophy and most extensive in primary lateral sclerosis. The most extensive patterns of fractional anisotropy reduction were observed over time in the voxel-based analysis, indicating progressive extra-motor white matter degeneration in limb- and bulbar onset amyotrophic lateral sclerosis and in progressive muscular atrophy. The observation of both upper motor and extra-motoneuron involvement in all phenotypes of motoneuron disease shortly after diagnosis suggests that these are all part of a single spectrum of multisystem neurodegenerative disease. Voxel-based analysis was more sensitive to detect longitudinal changes than diffusion tensor tractography of the corticospinal tract. Voxel-based analyses may be particularly valuable in the evaluation of motor and extra-motor white matter involvement in the early symptomatic stages of motoneuron disease, and for monitoring the spread of pathology over time.
    Brain 02/2011; 134(Pt 4):1211-28. · 10.23 Impact Factor
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    ABSTRACT: The trapeziometacarpal joint enables the prehensile function of the thumb. Unfortunately, this joint is vulnerable to osteoarthritis (OA) that typically affects the local shape of the trapezium. A novel, local statistical shape model is defined that employs a differentiable locality measure based on the weighted variance of point coordinates per mode. The simplicity of the function and the smooth derivative enable to quickly determine localized components for densely sampled surfaces. The method is employed to assess a set of 60 trapezia (38 healthy, 22 with OA). The localized components predominantly model regions affected by OA, contrary to shape variations found with PCA. Furthermore, identification of pathological trapezia based on the localized modes of variation is improved compared to PCA.
    Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. 01/2011; 14(Pt 2):360-7.
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    ABSTRACT: Patient studies based on diffusion tensor images (DTI) require spatial correspondence between subjects. We propose to obtain the correspondence from white matter tracts, by introducing a new method for nonrigid matching of white matter fiber tracts in DTI. The method boils down to point set registration that involves simultaneously clustering and matching of the data points. The tracts are implicitly warped to a common frame of reference to avoid the potential bias toward one of the datasets. The algorithm gradually refines from global to local registration, which is implemented through deterministic annealing. Special care was taken to incorporate the spatial relation between fiber points and the uncertainty in principal diffusion orientation. As a result, the computed clusters are oriented along the fiber tracts and discriminate between adjacent but distinct fiber tracts. This is validated on synthetic and clinical data. The root-mean-squared distance with respect to expert-annotated landmarks is low (3 mm). In contrast to a state-of-the-art nonrigid registration technique, the proposed method is more robust to residual misalignments in terms of measured fractional anisotropy values.
    IEEE Transactions on Biomedical Engineering 01/2011; 58(9):2431-2440. · 2.35 Impact Factor

Publication Stats

905 Citations
126.93 Total Impact Points

Institutions

  • 2002–2013
    • University of Amsterdam
      • • Department of Radiology
      • • Faculty of Medicine AMC
      Amsterdam, North Holland, Netherlands
  • 1998–2013
    • Delft University Of Technology
      • • Department of Imaging Science and Technology
      • • Faculty of Applied Sciences (AS)
      Delft, South Holland, Netherlands
  • 2003–2011
    • Academisch Medisch Centrum Universiteit van Amsterdam
      • Department of Radiology
      Amsterdam, North Holland, Netherlands
  • 2010
    • Philips
      Eindhoven, North Brabant, Netherlands
  • 2006–2007
    • Het Oogziekenhuis Rotterdam
      Rotterdam, South Holland, Netherlands
  • 1996–2001
    • VU University Amsterdam
      • Department of Physics and Astronomy
      Amsterdam, North Holland, Netherlands