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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: 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: 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; · 1.73 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: There is an ongoing debate on how to model diffusivity in fiber crossings. We propose an optimization framework for the selection of a dual tensor model and the set of diffusion weighting parameters b, such that both the diffusion shape and orientation parameters can be precisely as well as accurately estimated. For that, we have adopted the Cramér-Rao lower bound (CRLB) on the variance of the model parameters, and performed Monte Carlo simulations. We have found that the axial diffusion lambda(parallel) needs to be constrained, while an isotropic fraction can be modeled by a single parameter f(iso). Under these circumstances, the Fractional Anisotropy (FA) of both tensors can theoretically be independently estimated with a precision of 9% (at SNR = 25). Levenberg-Marquardt optimization of the Maximum Likelihood function with a Rician noise model approached this precision while the bias was insignificant. A two-element b-vector b = [1.0 3.5] x 10(3) mm(-2)s was found to be sufficient for estimating parameters of heterogeneous tissue with low error. This has allowed us to estimate consistent FA-profiles along crossing tracts. This work defines fundamental limits for comparative studies to correctly analyze crossing white matter structures.
IEEE transactions on medical imaging. 08/2010; 29(8):1504-15.
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ABSTRACT: The purpose of this study was to determine whether a low-fiber diet is necessary for optimal tagging-only bowel preparation for CT colonography.
Fifty consecutively enrolled patients received an iodine bowel preparation: 25 patients used a low-fiber diet and 25 used no special diet. One observer determined the tagging quality per segment on a 5-point scale (1, inhomogeneous tagging; 5, excellent preparation) and the largest size of untagged feces. Semiautomatic measurements of density and homogeneity of residual feces were performed. Patient acceptance was assessed with questionnaires. Per polyp sensitivity for polyps 6 mm in diameter and larger was calculated for two experienced observers.
Tagging quality was scored less than grade 5 in 15 segments (10%) in the low-fiber diet group and in 25 segments (17%) in the unrestricted diet group (p = 0.098). One piece of untagged feces 10 mm in diameter or larger was found in the low-fiber diet group, and 12 were found in the unrestricted diet group (p < 0.001). Automatic measurement of attenuation resulted in a mean value of 594 HU in the low-fiber diet group and 630 HU in the unrestricted diet group (p = 0.297). In the low-fiber diet group, 22% of patients indicated that the bowel preparation was extremely or severely burdensome; 8% of patients in the unrestricted diet group had this response (p = 0.19). Thirty-two polyps 6 mm in diameter or larger were found in the low-fiber diet group and 30 in the unrestricted diet group. Observer 1 had 84% and 77% sensitivity in detecting polyps 6 mm in diameter or larger in the low-fiber diet and unrestricted diet groups, respectively (p = 0.443), and observer 2 had 97% and 83% sensitivity (p = 0.099).
Use of a low-fiber diet in bowel preparation for CT colonography results in significantly less untagged feces and shows a trend toward better residue homogeneity.
American Journal of Roentgenology 07/2010; 195(1):W31-7. · 2.78 Impact Factor
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Ayso H de Vries,
Shandra Bipat,
Evelien Dekker,
Marjolein H Liedenbaum,
Jasper Florie,
Paul Fockens,
Roel van der Kraan,
Elizabeth M Mathus-Vliegen,
Johannes B Reitsma,
Roel Truyen, Frans M Vos,
Aeilko H Zwinderman,
Jaap Stoker
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ABSTRACT: To assess the variability and systematic differences in polyp measurements on optical colonoscopy and CT colonography.
Gastroenterologists measured 51 polyps by visual estimation, forceps comparison and linear probe. CT colonography observers randomly assessed polyp size two-dimensionally (abdominal and intermediate window) and three-dimensionally (manually and semi-automatically). Linear mixed models were used to assess the variability and systematic differences between CT colonography and optical colonoscopy techniques.
The variability of forceps and linear probe measurements was comparable and both showed less variability than measurement by visual assessment. Measurements by linear probe were 0.7 mm smaller than measurements by visual assessment or by forceps. The variability of all CT colonography techniques was lower than for measurements by forceps or visual assessment and sometimes lower (only 2D intermediate window and manual 3D) compared with measurements by linear probe. All CT colonography measurements judged polyps to be larger than optical colonoscopy, with differences ranging from 0.7 to 2.3 mm.
A linear probe does not reduce the measurement variability of endoscopists compared with the forceps. Measurement differences between observers on CT colonography were usually smaller than at optical colonoscopy. Polyps appeared larger when using various CT colonography techniques than when measured during optical colonoscopy.
European Radiology 06/2010; 20(6):1404-13. · 3.22 Impact Factor
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ABSTRACT: Today's computer aided detection systems for computed tomography colonography (CTC) enable automated detection and segmentation of colorectal polyps. We present a paradigm shift by proposing a method that measures the amount of protrudedness of a candidate object in a scale adaptive fashion. One of the main results is that the performance of the candidate detection depends only on one parameter, the amount of protrusion. Additionally the method yields correct polyp segmentation without the need of an additional segmentation step. The supervised pattern recognition involves a clear distinction between size related features and features related to shape or intensity. A Mahalanobis transformation of the latter facilitates ranking of the objects using a logistic classifier. We evaluate two implementations of the method on 84 patients with a total of 57 polyps larger than or equal to 6 mm. We obtained a performance of 95% sensitivity at four false positives per scan for polyps larger than or equal to 6 mm.
IEEE transactions on medical imaging. 03/2010; 29(3):688-98.
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ABSTRACT: Diagnosing of injuries of the wrist bones is problematic due to a highly complex and variable geometry. knowledge of variations of healthy bone shapes is essential to detect wrist pathologies, developing prosthetics and investigating biomechanical properties of the wrist joint. In previous literature various methods have been proposed to classify different scaphoid and lunate types. These classifications were mainly qualitative or were based on a limited number of manually determined surface points. The purposes of this study are to develop a quantitative, standardized description of the variations in the scaphoid and lunate and to investigate whether it is feasible to divide carpal bones in isolated shape categories based on statistical grounds. The shape variations of the scaphoid and lunate were described by constructing a statistical shape model (SSM) of healthy bones. SSM shape parameters were determined that describe the deviation of each shape from the mean shape. The first five modes of variation in the SSMs describe 60% of the total variance of the scaphoid and 57% of the lunate. Higher modes describe less than 5% of the variance per mode. The distributions of the parameters that characterize the bone shape variations along the modes do not significantly differ from a normal distribution. The SSM provides a description of possible shape variations and the distribution of scaphoid and lunate shapes in our population at an accuracy of approximately the voxel size (0.3x0.3x0.3mm(3)). The developed statistical shape model represents the previously qualitatively described variations of scaphoid and lunate. However, strict classifications based on shape differences are not feasible on statistical grounds.
Journal of biomechanics 02/2010; 43(8):1463-9. · 2.66 Impact Factor
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IEEE Trans. Med. Imaging. 01/2010; 29:1504-1515.
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10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, CCGrid 2010, 17-20 May 2010, Melbourne, Victoria, Australia; 01/2010
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IEEE Trans. Med. Imaging. 01/2010; 29:120-131.
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ABSTRACT: We present a computer-aided detection (CAD) system for computed tomography colonography that orders the polyps according to clinical relevance. The CAD system consists of two steps: candidate detection and supervised classification. The characteristics of the detection step lead to specific choices for the classification system. The candidates are ordered by a linear logistic classifier (logistic regression) based on only three features: the protrusion of the colon wall, the mean internal intensity, and a feature to discard detections on the rectal enema tube. This classifier can cope with a small number of polyps available for training, a large imbalance between polyps and non-polyp candidates, a truncated feature space, unbalanced and unknown misclassification costs, and an exponential distribution with respect to candidate size in feature space. Our CAD system was evaluated with data sets from four different medical centers. For polyps larger than or equal to 6 mm we achieved sensitivities of respectively 95%, 85%, 85%, and 100% with 5, 4, 5, and 6 false positives per scan over 86, 48, 141, and 32 patients. A cross-center evaluation in which the system is trained and tested with data from different sources showed that the trained CAD system generalizes to data from different medical centers and with different patient preparations. This is essential to application in large-scale screening for colorectal polyps.
IEEE transactions on medical imaging. 09/2009; 29(1):120-31.
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ABSTRACT: Comparing wrist shapes of different individuals requires alignment of these wrists into the same pose. Unconstrained registration of the carpal bones results in anatomically nonfeasible wrists. In this paper, we propose to constrain the registration using the shapes of adjacent bones, by keeping the width of the gap between adjacent bones constant. The registration is formulated as an optimization involving two terms. One term aligns the wrist bones by minimizing the distances between corresponding bone surfaces. The second term constrains the registration by minimizing the distances between adjacent sliding surfaces. The registration is based on the Iterative Closest Point algorithm. All bones are registered concurrently so that no bias is introduced towards any of the bones. The proposed registration method delivers anatomically correct configurations of the bones. The registration errors are in the order of the voxel size of the acquired CT data (0.3 x 0.3 x 0.3 mm(3)). The standard deviation in the widths of gaps between adjacent bones is in the order of 10% with an insignificant bias. This is a large improvement over the standard deviations of 30%-80% encountered in unconstrained registration. The value of this method is its capability of accurately registering joints in varying poses resulting in physiological joint configurations.
IEEE Transactions on Medical Imaging 06/2009; 28(12):1861-9. · 3.64 Impact Factor
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ABSTRACT: To determine whether childhood medulloblastoma and acute lymphoblastic leukemia (ALL) survivors have decreased white matter fractional anisotropy (WMFA) and whether WMFA is related to the speed of processing and motor speed.
For this study, 17 patients (6 medulloblastoma, 5 ALL treated with high-dose methotrexate (MTX) (4 x 5 g/m(2)) and 6 with low-dose MTX (3 x 2 g/m(2))) and 17 age-matched controls participated. On a 3.0-T magnetic resonance imaging (MRI) scanner, diffusion tensor imaging (DTI) was performed, and WMFA values were calculated, including specific regions of interest (ROIs), and correlated with the speed of processing and motor speed.
Mean WMFA in the patient group, mean age 14 years (range 8.9 - 16.9), was decreased compared with the control group (p = 0.01), as well as WMFA in the right inferior fronto-occipital fasciliculus (IFO) (p = 0.03) and in the genu of the corpus callosum (gCC) (p = 0.01). Based on neurocognitive results, significant positive correlations were present between processing speed and WMFA in the splenium (sCC) (r = 0.53, p = 0.03) and the body of the corpus callosum (bCC) (r = 0.52, p = 0.03), whereas the right IFO WMFA was related to motor speed (r = 0.49, p < 0.05).
White matter tracts, using a 3.0-T MRI scanner, show impairment in childhood cancer survivors, medulloblastoma survivors, and also those treated with high doses of MTX. In particular, white matter tracts in the sCC, bCC and right IFO are positively correlated with speed of processing and motor speed.
International journal of radiation oncology, biology, physics 01/2009; 74(3):837-43. · 4.59 Impact Factor
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IEEE Trans. Med. Imaging. 01/2009; 28:1861-1869.
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Proceedings of the 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Boston, MA, USA, June 28 - July 1, 2009; 01/2009
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Image Analysis, 16th Scandinavian Conference, SCIA 2009, Oslo, Norway, June 15-18, 2009. Proceedings; 01/2009
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ABSTRACT: The design of most ulnar head implants is currently not based on studies of anatomical variations. To enable prosthesis design based on anatomical features, a method is developed for the detection of the ulna surface that articulates with the radius head. The articulating surface is detected by combining partial articulating ulna surfaces detected in CT scans of different individuals in different poses. Correspondences between ulnae of different individuals are established through the construction of a statistical shape model (SSM) of the ulna head. The articulating surface is attached to this SSM, allowing the detection of articulating surfaces in ulnae that are not in the training set of the model. As a simple shape is desirable for prosthesis design, three quadratic surfaces were fitted to the articulating surfaces of 40 ulnae. The mean fitting error for the simplest surface, a cylinder, was 0.20 mm. As this error is smaller than the voxel size of 0.3 mm isotropic, it was concluded that the articulating ulna surface can be satisfactory approximated by a cylinder part.
Proceedings of the 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Boston, MA, USA, June 28 - July 1, 2009; 01/2009
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19th International Conference on Pattern Recognition (ICPR 2008), December 8-11, 2008, Tampa, Florida, USA; 01/2008
