Thomas Vetter

Universität Basel, Bâle, Basel-City, Switzerland

Are you Thomas Vetter?

Claim your profile

Publications (127)117.33 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: A novel stereoscopic image acquisition setup and a procedure for measuring multidimensional particle size distributions (nD PSDs) during crystallization based on image analysis are presented. Images of crystals in suspension passing a flow through cell are generated by two cameras which are arranged in an orthogonal manner. Particles are conveyed to the flow through cell using a sampling loop, thus allowing for online monitoring. Automated image analysis provides contour data which can be used to classify crystals into different generic particle model classes. For each type of particle size data is calculated and stored. Finally, time resolved nD PSD data can be calculated. The accuracy of this novel size measurement was confirmed by comparison to measurements obtained with a Coulter Multisizer. The non-invasive nature and repeatability of experiments are shown by monitoring populations of sodium chloride and of the β polymorph of l-glutamic acid under different conditions. Finally, crystal growth of acetaminophen during cooling crystallization is shown. In addition, a virtual test bench is used to study the measurement method in silico.
    Chemical Engineering Science. 01/2014; 105:155–168.
  • [Show abstract] [Hide abstract]
    ABSTRACT: Understanding crystal growth from solution is crucial to control the evolution of crystal morphologies. Experiments, molecular simulations, and theory were combined to examine the morphology of urea crystals grown in different solutions. To get a rational representation of all the possible habits a shape diagram is introduced in which the habit dependence on the relative growth rates is illustrated.
    Angewandte Chemie International Edition 10/2013; · 11.34 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: We present a method to compute the conditional distribution of a statistical shape model given partial data. The result is a "posterior shape model", which is again a statistical shape model of the same form as the original model. This allows its direct use in the variety of algorithms that include prior knowledge about the variability of a class of shapes with a statistical shape model. Posterior shape models then provide a statistically sound yet easy method to integrate partial data into these algorithms. Usually, shape models represent a complete organ, for instance in our experiments the femur bone, modeled by a multivariate normal distribution. But because in many application certain parts of the shape are known a priori, it is of great interest to model the posterior distribution of the whole shape given the known parts. These could be isolated landmark points or larger portions of the shape, like the healthy part of a pathological or damaged organ. However, because for most shape models the dimensionality of the data is much higher than the number of examples, the normal distribution is singular, and the conditional distribution not readily available. In this paper, we present two main contributions: First, we show how the posterior model can be efficiently computed as a statistical shape model in standard form and used in any shape model algorithm. We complement this paper with a freely available implementation of our algorithms. Second, we show that most common approaches put forth in the literature to overcome this are equivalent to probabilistic principal component analysis (PPCA), and Gaussian Process regression. To illustrate the use of posterior shape models, we apply them on two problems from medical image analysis: model-based image segmentation incorporating prior knowledge from landmarks, and the prediction of anatomically correct knee shapes for trochlear dysplasia patients, which constitutes a novel medical application. Our experiments confirm that the use of conditional shape models for image segmentation improves the overall segmentation accuracy and robustness.
    Medical image analysis 06/2013; 17(8):959-973. · 3.09 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: We present a novel method for nonrigid registration of 3D surfaces and images. The method can be used to register surfaces by means of their distance images, or to register medical images directly. It is formulated as a minimization problem of a sum of several terms representing the desired properties of a registration result: smoothness, volume preservation, matching of the surface, its curvature, and possible other feature images, as well as consistency with previous registration results of similar objects, represented by a statistical deformation model. While most of these concepts are already known, we present a coherent continuous formulation of these constraints, including the statistical deformation model. This continuous formulation renders the registration method independent of its discretization. The finite element discretization we present is, while independent of the registration functional, the second main contribution of this paper. The local discontinuous Galerkin method has not previously been used in image registration, and it provides an efficient and general framework to discretize each of the terms of our functional. Computational efficiency and modest memory consumption are achieved thanks to parallelization and locally adaptive mesh refinement. This allows for the first time the use of otherwise prohibitively large 3D statistical deformation models.
    Computational and Mathematical Methods in Medicine 01/2013; 2013:674273. · 0.79 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: We introduce a robust multi-object tracking for abstract multi-dimensional feature vectors. The Condensation and the Wavelet Approximated Reduced Vector Machine (W-RVM) approach are joined to spend only as much as necessary effort for easy to discriminate regions (Condensation) and measurement locations (W-RVM) of the feature space, but most for regions and locations with high statistical likelihood to contain the object of interest. The new 3D Cascaded Condensation Tracking (CCT) yields more than 10 times faster tracking than state-of-art detection methods. We demonstrate HCI applications by high resolution face tracking within a large camera scene with an active dual camera system.
    Computer Standards & Interfaces - CSI. 11/2012;
  • Thomas Albrecht, Thomas Vetter
    [Show abstract] [Hide abstract]
    ABSTRACT: We present a method to automatically reposition the fragments of a broken bone based on surface meshes segmented from CT scans. The result of this virtual fracture reduction is intended to be used as an operation plan for a medical procedure. Particularly in minimally invasive surgery like intramedullary nailing, the correct repositioning of bone fragments is not always apparent or visible without an operation plan. We propose to achieve automatic fracture reduction by fitting the bone fragments to an intact reference bone mesh with a modified Iterative Closest Point (ICP) algorithm. A suitable reference could be the same patient's contra-lateral bone. In the absence of a CT scan of this bone, we propose to use a statistical shape model as a reference. The shape model is automatically adapted to match the anatomy of the broken bone, apart from the bone's length, which has to be correctly initialized. Our experiments show that we can limit the rotational alignment error to below 5 degrees, compared to 15 degrees in current medical practice.
    Proceedings of the 2012 international conference on Mesh Processing in Medical Image Analysis; 10/2012
  • [Show abstract] [Hide abstract]
    ABSTRACT: Controlling the shape of crystals is of great practical relevance in fields like pharmacology and fine chemistry. Here we examine the paradigmatic case of urea which is known to crystallize from water with a needle-like morphology. To prevent this undesired effect, inhibitors that selectively favor or discourage the growth of specific crystal faces can be used. In urea the most relevant faces are the {001} and the {110} which are known to grow fast and slow, respectively. The relevant growth speed difference between these two crystal faces is responsible for the needle-like structure of crystals grown in water solution. To prevent this effect, additives are used to slow down the growth of one face relative to another, thus controlling the shape of the crystal. We study the growth of fast {001} and slow {110} faces in water solution and the effect of shape controlling inhibitors like biuret. Extensive sampling through molecular dynamics simulations provides a microscopic picture of the growth mechanism and of the role of the additives. We find a continuous growth mechanism on the {001} face, while the slow growing {110} face evolves through a birth and spread process, in which the rate-determining step is the formation on the surface of a two-dimensional crystalline nucleus. On the {001} face, growth inhibitors like biuret compete with urea for the adsorption on surface lattice sites; on the {110} face instead additives cannot interact specifically with surface sites and play a marginal sterical hindrance of the crystal growth. The free energies of adsorption of additives and urea are evaluated with advanced simulation methods (well-tempered metadynamics) allowing a microscopic understanding of the selective effect of additives. Based on this case study, general principles for the understanding of the anisotropic growth of molecular crystals from solutions are laid out. Our work is a step toward a rational development of novel shape-affecting additives.
    Journal of the American Chemical Society 09/2012; 134(41):17221-33. · 10.68 Impact Factor
  • The Insight Journal. 01/2012;
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, we introduce concepts to reduce the computational complexity of regression, which are successfully used for Support Vector Machines. To the best of our knowledge, we are the first to publish the use of a cascaded Reduced Set Vector approach for regression. The Wavelet-Approximated Reduced Vector Machine classifiers for face and facial feature point detection are extended to regression for efficient and robust head pose estimation. We use synthetic data, generated by the 3D Morph able Model, for optimal training sets and demonstrate results superior to state-of-the-art techniques. The new Wavelet Reduced Vector Regression shows similarly good results on natural data, gaining a reduction of the complexity by a factor of up to 560. The introduced Evolutionary Regression Tree uses coarse-to-fine loops of strongly reduced regression and classification up to most accurate complex machines. We demonstrate the Cascaded Condensation Tracking for head pose estimation for a large pose range up to +-90 degrees on videostreams.
    01/2012;
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Previous research has shown high cross-cultural consensus in personality trait judgments based on faces. However, the information that was provided in these studies included extrafacial features, such as hairstyle or clothes. Such styling information can be intentionally chosen by target persons to express who they are. Using a well-developed and validated Western face model, we were able to formalize the static facial information that is used to make certain personality trait judgments, namely, aggressiveness, extroversion, likeability, risk seeking, social skills, and trustworthiness judgments. We manipulated this information in photographs of Asian and Western faces with natural-looking results. Asian and Western participants identified the enhanced salience of all different personality traits in the faces. Asian participants, however, needed more time for this task. Moreover, faces with enhanced salience of aggressiveness, extroversion, social skills, and trustworthiness were better identified by Western than by Asian participants.
    Social Psychological and Personality Science. 11/2011; 2(6).
  • Source
    Thomas Vetter, Marco Mazzotti, Jörg Brozio
    [Show abstract] [Hide abstract]
    ABSTRACT: In the present study, the effect of the polymeric additive Pluronic F127 on the growth rate of Ibuprofen (IBU) crystals from ethanol–water mixtures and its temperature and additive concentration dependence is investigated quantitatively. It is found that the addition of Pluronic F127 (PF127) to the solvent mixture slows the growth rate. At a temperature of 15 °C and an initial supersaturation of 1.5, for instance, 4 and 8 wt % of PF127 lead to a growth rate of 70% and 55%, respectively, of the value without additive. To characterize the growth kinetics, seeded desupersaturation experiments are carried out and monitored using in situ measurement techniques such as attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy and focused beam reflectance measurement (FBRM). The solubility of IBU at different temperatures and PF127 concentrations is determined by using a multivariate calibration model for the ATR-FTIR signal. A population balance model describing the process is fitted to the experimental data by estimating parameters of the growth rate expression used. The growth rate was identified to be surface integration controlled. It is proposed that the additive causes changes in the growth rate due to isotropic adsorption of the polymer molecules on the crystal surfaces. The purity of the crystals grown in the presence of the additive is evaluated using high performance liquid chromatography (HPLC). It is shown that the PF127 used in the crystallization process is not incorporated into the crystals.
    Crystal Growth & Design. 08/2011; 11(9).
  • Source
    B. Amberg, T. Vetter
    [Show abstract] [Hide abstract]
    ABSTRACT: In video post-production it is often necessary to track interest points in the video. This is called off-line tracking, because the complete video is available to the algorithm and can be contrasted with on-line tracking, where an incoming stream is tracked in real time. Off-line tracking should be accurate and - if used interactively - needs to be fast, preferably faster than real-time. We describe a 50 to 100 frames per second off-line tracking algorithm, which globally maximizes the probability of the track given the complete video. The algorithm is more reliable than previous methods because it explains the complete frames, not only the patches of the final track, making as much use of the data as possible. It achieves efficiency by using a greedy search strategy with deferred cost evaluation, focusing the computational effort on the most promising track candidates while finding the globally optimal track.
    Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on; 07/2011
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Mirroring of missing facial parts and rapid prototyping of templates have become widely used in the manufacture of prostheses. However, mirroring is not applicable for central facial defects, and the manufacture of a template still requires labour-intensive transformation into the final facial prosthesis. We have explored innovative techniques to meet these remaining challenges. We used a morphable model of a face for the reconstruction of missing facial parts that did not have mirror images, and skin-coloured polyamide laser sintering for direct manufacture of the prosthesis. From the knowledge gleaned from a data set of 200 coloured, three-dimensional scans, we generated a missing nose that was statistically compatible with the remaining parts of the patient's face. The planned prosthesis was manufactured directly from biocompatible skin-coloured polyamide powder by selective laser sintering, and the prosthesis planning system produced a normal-looking reconstruction. The polyamide will need adjustable colouring, and we must be able to combine it with a self-curing resin to fulfil the requirements of realistic permanent use.
    British Journal of Oral and Maxillofacial Surgery 03/2011; 49(8):e67-71. · 2.72 Impact Factor
  • Source
    Brian Amberg, Thomas Vetter
    [Show abstract] [Hide abstract]
    ABSTRACT: Fitting statistical 2D and 3D shape models to images is necessary for a variety of tasks, such as video editing and face recognition. Much progress has been made on local fitting from an initial guess, but determining a close enough initial guess is still an open problem. One approach is to detect distinct landmarks in the image and initalize the model fit from these correspondences. This is difficult, because detection of landmarks based only on the local appearance is inherently ambiguous. This makes it necessary to use global shape information for the detections. We propose a method to solve the combinatorial problem of selecting out of a large number of candidate landmark detections the configuration which is best supported by a shape model. Our method, as opposed to previous approaches, always finds the globally optimal configuration. The algorithm can be applied to a very general class of shape models and is independent of the underlying feature point detector. Its theoretic optimality is shown, and it is evaluated on a large face dataset.
    IEEE International Conference on Computer Vision, ICCV 2011, Barcelona, Spain, November 6-13, 2011; 01/2011
  • Source
    Marcel Lüthi, Christoph Jud, Thomas Vetter
    [Show abstract] [Hide abstract]
    ABSTRACT: Hybrid registration schemes are a powerful alternative to fully automatic registration algorithms. Current methods for hybrid registration either include the landmark information as a hard constraint, which is too rigid and leads to difficult optimization problems, or as a soft-constraint, which introduces a difficult to tune parameter for the landmark accuracy. In this paper we model the deformations as a Gaussian process and regard the landmarks as additional information on the admissible deformations. Using Gaussian process regression, we integrate the landmarks directly into the deformation prior. This leads to a new, probabilistic regularization term that penalizes deformations that do not agree with the modeled landmark uncertainty. It thus provides a middle ground between the two aforementioned approaches, without sharing their disadvantages. Our approach works for a large class of different deformation priors and leads to a known optimization problem in a Reproducing Kernel Hilbert Space.
    Pattern Recognition - 33rd DAGM Symposium, Frankfurt/Main, Germany, August 31 - September 2, 2011. Proceedings; 01/2011
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In this chapter, we present the Morphable Model, a three-dimensional (3D) representation that enables the accurate modeling of any illumination and pose as well as the separation of these variations from the rest (identity and expression). The Morphable Model is a generative model consisting of a linear 3D shape and appearance model plus an imaging model, which maps the 3D surface onto an image. The 3D shape and appearance are modeled by taking linear combinations of a training set of example faces. We show that linear combinations yield a realistic face only if the set of example faces is in correspondence. A good generative model should accurately distinguish faces from non faces. This is encoded in the probability distribution over the model parameters, which assigns a high probability to faces and a low probability to non faces. The distribution is learned together with the shape and appearance space from the training data.
    12/2010: pages 137-168;
  • Source
    Matthias Amberg, Marcel Lüthi, Thomas Vetter
    [Show abstract] [Hide abstract]
    ABSTRACT: In this paper we present a completely automated method for the segmentation of bone and cartilage in MR images of the knee. Our segmentation method is based on fitting a statistical deformation model, which was built from a set of labeled training images of the knee. The resulting deformation field is used to transfer a given segmentation from a reference image onto the target image to be segmented. To enlarge the flexibility of the deformation model in a controlled way, we use the idea of localized fitting, i.e. we fit the deformation model to local regions separately and combine the individual deformation fields. We applied our procedure to a set of images that were provided for the MICCAI 2010 workshop "Medical Image Analysis for the Clinic". Our results show that our approach yields good results around the interface of tibia and femur. The results also reveal a number of problems that occur with a naive application of this method to the problem of knee seg-mentation. In particular it turns out that the quality of the segmentation deteriorates near the boundary of the images.
    01/2010;
  • Michel Kempkes, Thomas Vetter, Marco Mazzotti
    [Show abstract] [Hide abstract]
    ABSTRACT: In this work, a technique capable of restoring bidimensional particle size distributions from images of the particles in suspension is applied to the seeded cooling crystallization of paracetamol from water. The effects of cooling rate and stirring rate on the final particle size and shape are studied and the average growth rates along different directions of particles are found to be strongly dependend on supersaturation. This observation is in line with previous studies, though in this work it has been established for the first time using populations of particles. The technique was capable of quantifying changes in particle size and shape, indicating particle sizes and shapes that correlated well with observations from electron microscopy images.
    Chemical Engineering Research & Design - CHEM ENG RES DES. 01/2010; 88(4):447-454.
  • Michel Kempkes, Thomas Vetter, Marco Mazzotti
    [Show abstract] [Hide abstract]
    ABSTRACT: In this work a method is presented to acquire 3D size information on particles in suspension. An experimental setup capable of acquiring two images from the same particle at different angles is presented. These images are then processed to yield a 4D measurement called axis length distribution (ALD). Using a measurement model and a restoration algorithm, the 3D particle size distribution (PSD) is reconstructed. The technique is applied to characterize the 3D PSD of ascorbic acid crystallized from methanol and of βl-glutamic acid crystals in water. The shape of these particles determined by the algorithm was found to compare well with observations from electron microscopy images.
    Chemical Engineering Science - CHEM ENG SCI. 01/2010; 65(4):1362-1373.
  • Source
    Matthias Amberg, Marcel Lüthi, Thomas Vetter
    [Show abstract] [Hide abstract]
    ABSTRACT: Fitting statistical models is a widely employed technique for the segmentation of medical images. While this approach gives impressive results for simple structures, shape models are often not flexible enough to accurately represent complex shapes. We present a fitting approach, which increases the model fitting accuracy without requiring a larger training data-set. Inspired by a local regression approach known from statistics, our method fits the full model to a neighborhood around each point of the domain. This increases the model’s flexibility considerably without the need to introduce an artificial segmentation of the structure. By adapting the size of the neighborhood from small to large, we can smoothly interpolate between localized fits, which accurately map the data but are more prone to noise, and global fits, which are less flexible but constrained to valid shapes only. We applied our method for the segmentation of teeth from 3D cone-beam ct-scans. Our experiments confirm that our method consistently increases the precision of the segmentation result compared to a standard global fitting approach.
    Pattern Recognition - 32nd DAGM Symposium, Darmstadt, Germany, September 22-24, 2010. Proceedings; 01/2010

Publication Stats

5k Citations
117.33 Total Impact Points

Institutions

  • 2003–2013
    • Universität Basel
      • Department of Mathematics and Computer Science
      Bâle, Basel-City, Switzerland
  • 2007
    • General Motors Company
      Detroit, Michigan, United States
  • 1994–2003
    • Massachusetts Institute of Technology
      • • Center for Biological and Computational Learning
      • • Department of Brain and Cognitive Sciences
      Cambridge, MA, United States
    • Office of Naval Research
      Arlington, Virginia, United States
  • 2002
    • University of Freiburg
      Freiburg, Baden-Württemberg, Germany
  • 1994–2002
    • Max Planck Institute for Biological Cybernetics
      Tübingen, Baden-Württemberg, Germany
  • 1999
    • University of Texas at Dallas
      • School of Behavioral and Brain Sciences
      Richardson, Texas, United States