Marco Loog

Associate Professor

The Image Group
DIKU
University of Copenhagen
Universitetsparken 1
DK-2100 Copenhagen
Denmark

e-mail : loog@diku.dk
telephone : +45 35 32 14 00
fax : + 45 35 32 14 01

Research Interests

Topics of interest include, but are not limited to, linear dimensionality reduction, copulas, active shape models, presegmentations, diffusion equations, feature extraction & selection, fixed point theorems, relaxation labeling, educated guessing, IPMs, similarity approaches, the structure of blobs, energy minimization formulations, image processing and analysis, folklore theorems, linear embeddings, ugly ducklings, reaction-diffusion equations, QP, morphology, topology, nonparametric statistics, non-Euclidean geometry, distribution theory, inductive learning, support blob machines, detecting abnormalities [wherever], provable conjectures, static probability fusion, dependent component analysis, LDA, saliency, linear programming, differential geometry, \pi, e, \Gamma, and, \zeta, structural pattern recognition, CCA, support vectors, time stretching, fundamentals of image analysis, robust statistics, Kolmogorov complexity, machine learning, combining classifiers, order preservation, kernel methods, least committed approaches, GCV, scale space theory, discriminant analysis, black math, natural image statistics, image segmentation, pixel classifiers, Bayes point machines, instantaneous frequency, transmutation [back & forth], speech processing, nonlinear dimensionality reduction, information distance, naive Bayesianity, signal detection theory, pseudo-linear scale spaces, density estimation, heteroscedastic extensions, small samples, Fourier transforms, multi-scale information fusion, approximate pairwise accuracy criteria, MRFs, outlier detection, toroidal lattices, meta-pattern recognition, NP=P,... or not, catastrophe theory, maxent approaches, Bayesian statistics, non-Bayesian statistics, signal processing, time-frequency theory, random field theory, pattern theory, and, of course, free lunches, the statistical analysis of dirty pictures... and the improvement of statistical pattern recognition methods and their use in image processing and analysis

List of Publications

Journal articles

M. Loog. On an alternative formulation of the Fisher criterion that overcomes the small sample problem. Pattern Recognition, 40(6):1753– 1755, 2007

M. Loog, B. van Ginneken, and A.M.R. Schilham. Filter learning: application to suppression of bony structures from chest radiographs. Medical Image Analysis, accepted, 2006
A.K. Qin, P.N. Suganthan, and M. Loog. Generalized null space uncorrelated Fisher discriminant analysis for linear dimensionality reduction. Pattern Recognition, 39(9):1805-1808, 2006
R.P.W. Duin, M. Loog, and T.K. Ho. [editorial] Recent submissions in linear dimensionality reduction and face recognition. Pattern Recognition Letters, 27(7):707-708, 2006
M. Loog and B. van Ginneken. Segmentation of the posterior ribs in chest radiographs using iterated contextual pixel classification. IEEE Transactions on Medical Imaging, 25(5):602-611, 2006
B. van Ginneken, M.B. Stegmann, and M. Loog. Segmentation of anatomical structures in chest radiographs using supervised methods: A comparative study on a public database. Medical Image Analysis, 10(1):19-40, 2006
A.M.R. Schilham, B. van Ginneken, and M. Loog. A computer-aided diagnosis system for detection of lung nodules in chest radiographs with an evaluation on a public database. Medical Image Analysis, 10(2):247-258, 2006

M. Loog, B. van Ginneken, and R.P.W. Duin. Dimensionality reduction of image features using the canonical contextual correlation projection. Pattern Recognition, 38(12):2409-2418, 2005
A.K. Qin, P.N. Suganthan, and M. Loog. Uncorrelated heteroscedastic LDA based on the weighted pairwise Chernoff criterion. Pattern Recognition, 38(4):613–616, 2005

M. Loog and R.P.W. Duin. Linear dimensionality reduction via a heteroscedastic extension of LDA: The Chernoff criterion. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(6):732–739, 2004
M. Loog, R.P.W. Duin, and M.A. Viergever. The MDF discrimination measure: Fisher in disguise. Neural Networks, 17(4):563–566, 2004

M. Loog, R.P.W. Duin, and R. Haeb-Umbach. Multiclass linear dimension reduction by weighted pairwise Fisher criteria. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(7):762–766, 2001

Publicatons in conference and workshop proceedings

M. Loog. The jet metric. International Conference on Scale Space and Variational Methods in Computer Vision, Lecture Notes in Computer Science, Springer, accepted, 2007
M. Loog and F.B. Lauze. Blur invariant image priors. International Conference on Scale Space and Variational Methods in Computer Vision, Lecture Notes in Computer Science, Springer, accepted, 2007
K. Steenstrup Pedersen, M. Loog, and B. Markussen. Generic maximum likely scale selection. International Conference on Scale Space and Variational Methods in Computer Vision, Lecture Notes in Computer Science, Springer, accepted, 2007
K.S. Pedersen, M. Loog, P. van Dorst. Salient point and scale detection by minimum likelihood. JMLR Workshop and Conference Proceedings, volume 1, Gaussian Processes in Practice, 2007
J. Raundahl, M. Loog, and M. Nielsen. Evaluation of four mammographic density measures on HRT data. SPIE Medical Imaging, 2007

E.B. Dam, J. Folkesson, M. Loog, P. Pettersen, and C. Christiansen. Efficient automatic cartilage segmentation. MICCAI Joint Disease Workshop,published , 2006
K. Steenstrup Pedersen, P. van Dorst, and M. Loog. Minimum likelihood image feature and scale detection based on the Brownian image model. Proceedings of the Gaussian Processes in Practice Workshop, published, 2006
M. Loog. Conditional linear discriminant analysis. 18th International Conference on Pattern Recognition, ICPR, published, 2006
M. Loog. Generic blind source separation using second-order local statistics. 6th Joint IAPR International Workshops SSPR 2006 and SPR 2006 [S+SSPR 2006], volume 4109 of Lecture Notes in Computer Science, 2006
A.K. Qin, P.N. Suganthan, and M. Loog. Efficient feature extraction based on regularized uncorrelated Chernoff discriminant analysis. 18th International Conference on Pattern Recognition, ICPR, 2006
M. Loog and D. de Ridder. Local discriminant analysis. 18th International Conference on Pattern Recognition, ICPR, 2006
J. Raundahl, M. Loog, and M. Nielsen. Understanding Hessian-based density scoring. 8th International Workshop on Digital Mammography, Lecture Notes in Computer Science, 2006
M. Loog and B. van Ginneken. Bony structure suppression in chest radiographs. 2nd Workshop on Computer Vision Approaches to Medical Image Analysis, volume 4241 of Lecture Notes in Computer Science, 2006
J. Raundahl, M. Loog, and M. Nielsen. Mammographic density measured as changes in tissue structure caused by HRT. SPIE Medical Imaging, 2006

M. Loog, K. Steenstrup Pedersen, and B. Markussen. Maximum likely scale estimation. DSSCV 2005, International Workshop on Deep Structure, Singularities, and Computer Vision, 2005
B. Markussen, K Steenstrup Pedersen, and M. Loog. A scale invariant covariance structure on jet space. DSSCV 2005, International Workshop on Deep Structure, Singularities, and Computer Vision, 2005
A.K. Qin, S.Y.M. Shi, P.N. Suganthan, and M. Loog. Enhanced direct linear discriminant analysis or feature extraction on high dimensional data. AAAI-05, Twentieth National Conference on Artificial Intelligence, 2005

M. Loog and B. van Ginneken. Static posterior probability fusion for signal detection: Applications in the detection of interstitial diseases in chest radiographs. 17th International Conference on Pattern Recognition, ICPR, 2004
D. de Ridder, M. Loog, and M.J.T. Reinders. Local Fisher embedding. 17th International Conference on Pattern Recognition, ICPR, 2004
B. van Ginneken and M. Loog. Pixel position regression–application to medical image segmentation. 17th International Conference on Pattern Recognition, ICPR, 2004
E.B. Dam, M. Loog, and M.M.J. Letteboer. Integrating automatic and interactive brain tumor segmentation. 17th International Conference on Pattern Recognition, ICPR, 2004
M. Loog. Support blob machines: The sparsification of scale space. European Conference on Computer Vision, ECCV 2004, pages 14–24, 2004
M. Loog, B. van Ginneken, and R.P.W. Duin. Dimensionality reduction by canonical contextual correlation projections. European Conference on Computer Vision, ECCV 2004, pages 562–573, 2004
M. Loog, B. van Ginneken, and M. Nielsen. Detection of interstitial lung disease in PA chest radiographs. SPIE Medical Imaging, 2004
M. Niemeijer, J.J. Staal, B. van Ginneken, M. Loog, and M.D. Abràmoff. Comparative study of retinal vessel segmentation methods on a new publicly available database. SPIE Medical Imaging, 2004

M. Loog, M. Lillholm, M. Nielsen, and M.A. Viergever. Gaussian scale space from insufficient image information. 4th International Conference on Scale-Space theories in Computer Vision, volume 2695 of Lecture Notes in Computer Science, pages 757–769, Springer, 2003
M. Loog, B. van Ginneken, and M.A. Viergever. Segmenting the posterior ribs in chest radiographs by iterated contextual pixel classification. SPIE Medical Imaging, volume 5032, pages 609–618. SPIE 2003
M. de Bruijne, B. van Ginneken, W.J. Niessen, M. Loog, and M.A. Viergever. Model-based segmentation of abdominal aortic aneurysms in CTA images. SPIE Medical Imaging, volume 5032, pages 1560–1571. SPIE 2003
B. van Ginneken, M. de Bruijne, M. Loog, and M.A. Viergever. Interactive shape models. SPIE Medical Imaging, volume 5032, pages 1206–1216. SPIE 2003
A.M.R. Schilham, B. van Ginneken, and M. Loog. Multi-scale nodule detection in chest radiographs. Medical Image Computing and Computer-Assisted Intervention, volume 2878 of Lecture Notes in Computer Science, pages 602–609. MICCAI 2003
A.M.R. Schilham, B. van Ginneken, and M. Loog. Influence of the number of training samples for computer-aided detection of lung nodules in chest radiographs. Radiological Society of North America, pages 523–524, 2003

M. Loog and B. van Ginneken. Supervised segmentation by iterated contextual pixel classification. 16th International Conference on Pattern Recognition, volume 2, pages 925–928. IEEE Computer Society Press, August 2002
M. Loog and R.PW. Duin. Non-iterative heteroscedastic linear dimension reduction for two-class data: From Fisher to Chernoff. 4th Joint IAPR International Workshops SSPR 2002 and SPR 2002 [S+SSPR 2002], pages 508–517 IAPR, Springer-Verlag, August 2002

M. Loog, J.J. Duistermaat, and L.M.J. Florack. On the behavior of spatial critical points under Gaussian blurring: A folklore theorem and scale-space constraints. 3th International Conference on Scale-Space Theories in Computer Vision, volume 2106 of Lecture Notes in Computer Science, pages 183–192. Scale Space 2001

M. Loog and R. Haeb-Umbach. Multi-class linear dimension reduction by generalized Fisher criteria. International Conference on Spoken Language Processing 2000, volume 2, Beijing, People's Republic of China, 2000. ICSLP 2000
R.P.W. Duin, M. Loog, and R. Haeb-Umbach. Multi-class linear feature extraction by nonlinear PCA. 15th International Conference on Pattern Recognition, volume 2, pages 398–401, Barcelona, Spain, 2000. ICPR 2000

R. Haeb-Umbach and M. Loog. An investigation of cepstral parameterisations for large vocabulary speech recognition. 6th European Conference On Speech Communication And Technology, pages 1323–1326, Budapest, Hungary, 1999. EUROSPEECH '99

Patents

J. Raundahl, M. Loog, and M. Nielsen. Estimation of breast cancer risk, UK Patent Application, No. 0602739.5, filed February 10, 2006

Other publications

M. Loog. Supervised dimensionality reduction and contextual pattern recognition in medical image processing. Ph.D. thesis, Image Sciences Institute, Utrecht University, 2004

M. Loog. Approximate pairwise accuracy criteria for multiclass linear dimension reduction: generalisations of the Fisher criterion. Number 44 in WBBM Report Series. Delft University Press, Delft, 1999

Collaborators, Coauthors, Cocoauthors, and Conspirators

M.D. Abràmoff, University of Iowa, Iowa, USA
M. de Bruijne, IT University of Copenhagen, Denmark
C. Christiansen, Center for Clinical and Basic Research, Denmark
E.B. Dam, IT University of Copenhagen, Denmark
P. van Dorst, Eindhoven University of Technology, The Netherlands
R.P.W. Duin, Delft University of Technology, The Netherlands
J.J. Duistermaat, Utrecht University, The Netherlands
L.M.J. Florack, Eindhoven University of Technology, The Netherlands
J. Folkesson, IT University of Copenhagen, Denmark
B. van Ginneken, Image Sciences Institute, The Netherlands
R. Haeb-Umbach, University of Paderborn, Germany
T.K. Ho, Bell Laboratories, New Jersey, USA
A. Kuijper, Johann Radon Institute, Linz, Austria
F.B. Lauze, IT University of Copenhagen, Denmark
M.M.J. Letteboer, Image Sciences Institute, The Netherlands
M. Lillholm, University College London, United Kingdom
B. Markussen, Royal Veterinary and Agricultural University, Denmark
M. Nielsen, IT University of Copenhagen, Denmark
M. Niemeijer, Image Sciences Institute, The Netherlands
W.J. Niessen, Erasmus Medical Center, The Netherlands
K. Steenstrup Pedersen, IT University of Copenhagen, Denmark
P. Pettersen, Center for Clinical and Basic Research, Denmark
A.K. Qin, Nanyang Technological University, Singapore
J. Raundahl, IT University of Copenhagen, Denmark
M.J.T. Reinders, Delft University of Technology, The Netherlands
D. de Ridder, Delft University of Technology, The Netherlands
A.M.R. Schilham, Image Sciences Institute, The Netherlands
S.Y.M. Shi, Nanyang Technological University, Singapore
J.J. Staal, Barco, United Kingdom
M. Stegmann, Technical University of Denmark, Denmark
P.N. Suganthan, Nanyang Technological University, Singapore
M.A. Viergever, Image Sciences Institute, The Netherlands

Professional Service

Reviewer for journals

Electronic Letters on Computer Vision and Image Analysis
IEEE Signal Processing Letters
IEEE Transactions on Antennas and Propagation
IEEE Transactions on Image Processing
IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Medical Imaging
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Signal Processing
IEEE Transactions on Systems, Man, and Cybernetics—Part B: Cybernetics
IEE Proceedings Vision, Image and Signal Processing
Information Fusion
International Journal of Pattern Recognition and Artificial Intelligence
Journal of Computer Science and Technology
Journal of Multivariate Analysis
Neural Computation
Neural Networks
Optical Engineering
Pattern Analysis and Applications
Pattern Recognition
Pattern Recognition Letters
Proceedings of the Royal Society A

Program Committee

International Conference on Intelligent Computing [ICIC], 2007
International Conference on Pattern Recognition [ICPR], 2006

Publication Chair

International Conference on Intelligent Computing [ICIC], 2007

Reviewer for conferences and workshops

International Conference on Pattern Recognition [ICPR], 2006
Medical Image Computing and Computer-Assisted Intervention [MICCAI], 2006
International Workshop on Statistical Techniques in Pattern Recognition [SPR], 2006
European Conference on Computer Vision [ECCV], 2006
Medical Image Computing and Computer-Assisted Intervention [MICCAI], 2005
International Conference on Advances in Pattern Recognition [ICAPR], 2005
International Workshop on Deep Structure, Singularities, and Computer Vision [DSSCV], 2005
International Conference on Computer Vision [ICCV], 2005
International Workshop on Statistical Techniques in Pattern Recognition [SPR], 2004
Medical Image Computing and Computer-Assisted Intervention [MICCAI], 2004
International Conference on Computer Vision and Pattern Recognition [CVPR], 2003
International Conference on Scale Space Theories in Computer Vision, 2003