Frans M Vos

Delft University of Technology, Delft, South Holland, Netherlands

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Publications (82)95.81 Total impact

  • Experimental Gerontology 08/2015; 68. DOI:10.1016/j.exger.2015.01.020 · 3.53 Impact Factor
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    ABSTRACT: Registration of images in the presence of intra-image signal fluctuations is a challenging task. The definition of an appropriate objective function measuring the similarity between the images is crucial for accurate registration. This paper introduces an objective function that embeds local phase features derived from the monogenic signal in the modality independent neighborhood descriptor (MIND). The image similarity relies on the autocorrelation of local structure (ALOST) which has two important properties: (1) low sensitivity to space-variant intensity distortions (e.g. differences in contrast enhancement in MRI); (2) high distinctiveness for 'salient' image features such as edges. The ALOST method is quantitatively compared to the MIND approach based on three different datasets: thoracic CT images, synthetic and real abdominal MR images. The proposed method outperformed the NMI and MIND similarity measures on these three datasets. The registration of dynamic contrast enhanced and post-contrast MR images of patients with Crohn's disease led to relative contrast enhancement measures with the highest correlation (r=0.56) to the Crohn's disease endoscopic index of severity.
    IEEE Transactions on Medical Imaging 07/2015; DOI:10.1109/TMI.2015.2455416 · 3.80 Impact Factor
  • IEEE International Symposium on Biomedical Imaging; 04/2015
  • Zhang Li · Lucas J van Vliet · Jaap Stoker · Frans M Vos
    SPIE Medical Imaging; 02/2015
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    ABSTRACT: This paper studies a novel method to compensate for respiratory and peristaltic motions in abdominal Dynamic Contrast Enhanced MRI. The method consists of two steps: (1) expiration-phase 'template' construction and retrospective gating of the data to the template; (2) non-rigid registration of the gated volumes. Landmarks annotated by three experts were used to directly assess the registration performance. A tri-exponential function fit to time intensity curves from regions of interest was used to indirectly assess the performance. One of the parameters of the tri-exponential fit was used to quantify the contrast enhancement. Our method achieved a mean target registration error (MTRE) of 2.12 mm, 2.27 mm and 2.33mm with respect to annotations by expert, which was close to the average inter-observer variability (2.07mm). A state-of-the-art registration method achieved a MTRE of 2.83-3.10 mm. The correlation coefficient of the contrast enhancement parameter to the Crohn's Disease Endoscopic Index of Severity (r = 0.60, p = 0.004) was higher than the correlation coefficient for the Relative Contrast Enhancement measurements values of two observers (r(Observer 1) = 0.29, p =0.2; r(Observer 2) = 0.45, p = 0.04). Direct and indirect assessments show that the expiration-based gating and a non-rigid registration approach effectively corrects for respiratory motion and peristalsis. The method facilitates improved enhancement measurement in the bowel wall in patients with Crohn's disease.
    IEEE transactions on bio-medical engineering 12/2014; 62(4). DOI:10.1109/TBME.2014.2385307 · 2.23 Impact Factor
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    ABSTRACT: The Fast Spoiled Gradient Echo (FSPGR) sequence is often used in MRI to create T1-weighted images. The signal intensity generated by this sequence depends on the applied flip angle. Knowing the correct flip angle is essential for the determination of T1-maps by means of an FSPGR based Variable Flip Angle (VFA) approach. Also, quantitatively determining the concentration of contrast agent in case of Dynamic Contrast Enhanced MRI (DCE-MRI) requires knowledge of the applied flip angle. In both cases, the B1-field (in)homogeneity significantly affects the results. In this paper, we present a new method to obtain both the T1-map and B1-inhomogeneity map using scans that can each be acquired within a breath-hold. We combine two short sequences for T1 quantification: Variable Flip Angle and Look-Locker (LL). The T1-maps obtained from the LL data were used to estimate the B1-inhomogeneity inherently present in the VFA data, which was then used to correct for the VFA method’s inaccurate flip angles. This way, a reliable T1-map could be computed, which was validated using both in vitro and in vivo scans. The in vitro results show that the procedure yields a substantially smaller mean deviation in T1 from the T1 measurement’s gold standard (the Inversion Recovery method), while the in vivo results show both a more accurate estimation of T1 and a reduction of the influence of the B1-inhomogeneity on the signal intensity.
    Magnetic Resonance Imaging 11/2014; 33(3). DOI:10.1016/j.mri.2014.10.008 · 2.02 Impact Factor
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    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. DOI:10.2214/AJR.12.10341 · 2.74 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.
    09/2013; 32(12). DOI:10.1109/TMI.2013.2282124
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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; 24(3). DOI:10.1007/s00330-013-3015-7 · 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; 60(11). DOI:10.1109/TBME.2013.2262046 · 2.23 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; 76(1). DOI:10.1016/j.neuroimage.2013.03.015 · 6.36 Impact Factor
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    ABSTRACT: Scientists, engineers and physicians are used to analyze 3D data with slice-based visualizations. Radiologists for example are trained to read slices of medical imaging data. Despite the numerous examples of sophisticated 3D rendering techniques, domain experts, who still prefer slice-based visualization do not consider these to be very useful. Since 3D renderings have the advantage of providing an overview at a glance, while 2D depictions better serve detailed analyses, it is of general interest to better combine these methods. Recently there have been attempts to bridge this gap between 2D and 3D renderings. These attempts include specialized techniques for volume picking in medical imaging data that result in repositioning slices. In this paper, we present a new volume picking technique called WYSIWYP (“what you see is what you pick”) that, in contrast to previous work, does not require pre-segmented data or metadata and thus is more generally applicable. The positions picked by our method are solely based on the data itself, the transfer function, and the way the volumetric rendering is perceived by the user. To demonstrate the utility of the proposed method, we apply it to automated positioning of slices in volumetric scalar fields from various application areas. Finally, we present results of a user study in which 3D locations selected by users are compared to those resulting from WYSIWYP. The user study confirms our claim that the resulting positions correlate well with those perceived by the user.
    IEEE Transactions on Visualization and Computer Graphics 12/2012; 18(12). DOI:10.1109/TVCG.2012.292 · 1.92 Impact Factor
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    ABSTRACT: Thin layers of tissue and residue are easily misclassified by current electronic cleansing methods for CT colonography. Thereby holes are introduced in the colon wall that hamper visualization and auto-mated polyp detection. We present a thin layer model to detect and characterize such layers to support electronic cleansing. It is shown that the model sustains robust estimation of the location and thickness of thin layers. A lower bound on the thickness exists and was found to be 1.0 mm for our data.
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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.
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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.
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    Jeroen A.W. Tielbeek · Frans M Vos · Jaap Stoker
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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; 37(6). DOI:10.1007/s00261-011-9822-x · 1.73 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. DOI:10.1109/TMI.2011.2174159 · 3.80 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

Publication Stats

817 Citations
95.81 Total Impact Points


  • 2000–2015
    • Delft University of Technology
      • • Faculty of Applied Sciences (AS)
      • • Applied Geophysics and Petrophysics
      Delft, South Holland, Netherlands
  • 2007–2013
    • University of Amsterdam
      • Department of Radiology
      Amsterdamo, North Holland, Netherlands
  • 2010
    • Philips
      Eindhoven, North Brabant, Netherlands
  • 2001
    • Erasmus Universiteit Rotterdam
      • Department of Radiology
      Rotterdam, South Holland, Netherlands