Marco Loog

Summary

Affiliation: IT University of Copenhagen
Country: Denmark

Publications

  1. ncbi request reprint Segmentation of the posterior ribs in chest radiographs using iterated contextual pixel classification
    Marco Loog
    Image Sciences Institute, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands
    IEEE Trans Med Imaging 25:602-11. 2006
  2. ncbi request reprint Filter learning: application to suppression of bony structures from chest radiographs
    M Loog
    The Image Group, IT University of Copenhagen, Rued Langgaards Vej 7, 2300 Copenhagen S, Denmark
    Med Image Anal 10:826-40. 2006
  3. ncbi request reprint Image dissimilarity-based quantification of lung disease from CT
    Lauge Sørensen
    The Image Group, Department of Computer Science, University of Copenhagen, Denmark
    Med Image Comput Comput Assist Interv 13:37-44. 2010
  4. ncbi request reprint A computer-aided diagnosis system for detection of lung nodules in chest radiographs with an evaluation on a public database
    Arnold M R Schilham
    Image Sciences Institute, University Medical Center Utrecht, The Netherlands
    Med Image Anal 10:247-58. 2006
  5. doi request reprint Linear dimensionality reduction via a heteroscedastic extension of LDA: the Chernoff criterion
    Marco Loog
    Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
    IEEE Trans Pattern Anal Mach Intell 26:732-9. 2004
  6. ncbi request reprint Segmentation of anatomical structures in chest radiographs using supervised methods: a comparative study on a public database
    Bram van Ginneken
    Image Sciences Institute, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
    Med Image Anal 10:19-40. 2006
  7. doi request reprint On combining computer-aided detection systems
    Meindert Niemeijer
    University Medical Center Utrecht, Image Sciences Institute, 3584 CX Utrecht, The Netherlands
    IEEE Trans Med Imaging 30:215-23. 2011
  8. ncbi request reprint A family of principal component analyses for dealing with outliers
    J Eugenio Iglesias
    Department of Computer Science, University of Copenhagen, Denmark
    Med Image Comput Comput Assist Interv 10:178-85. 2007
  9. doi request reprint On distributional assumptions and whitened cosine similarities
    Marco Loog
    Pattern Recognition Group, Faculty of Elctrical Engineering, Mathematics and Computer Science, Delft Unversity of Technology, Delf, The Netherlands
    IEEE Trans Pattern Anal Mach Intell 30:1114-5. 2008
  10. ncbi request reprint Localized maximum entropy shape modelling
    Marco Loog
    Department of Computer Science, Nordic Bioscience A S, University of Copenhagen, Herlev, Copenhagen, Denmark
    Inf Process Med Imaging 20:619-29. 2007

Detail Information

Publications13

  1. ncbi request reprint Segmentation of the posterior ribs in chest radiographs using iterated contextual pixel classification
    Marco Loog
    Image Sciences Institute, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands
    IEEE Trans Med Imaging 25:602-11. 2006
    ..In a sixfold cross-validation experiment, ICPC achieves a classification accuracy of 0.86 +/- 0.06, as compared to 0.94 +/- 0.02 for the second human observer...
  2. ncbi request reprint Filter learning: application to suppression of bony structures from chest radiographs
    M Loog
    The Image Group, IT University of Copenhagen, Rued Langgaards Vej 7, 2300 Copenhagen S, Denmark
    Med Image Anal 10:826-40. 2006
    ....
  3. ncbi request reprint Image dissimilarity-based quantification of lung disease from CT
    Lauge Sørensen
    The Image Group, Department of Computer Science, University of Copenhagen, Denmark
    Med Image Comput Comput Assist Interv 13:37-44. 2010
    ..817. This is significantly better compared to combining individual region classifications into an overall image classification, and compared to common computerized quantitative measures in pulmonary CT...
  4. ncbi request reprint A computer-aided diagnosis system for detection of lung nodules in chest radiographs with an evaluation on a public database
    Arnold M R Schilham
    Image Sciences Institute, University Medical Center Utrecht, The Netherlands
    Med Image Anal 10:247-58. 2006
    ..For four false positives, this increases to 67%. This is close to the previously reported 70% detection rate of the radiologists...
  5. doi request reprint Linear dimensionality reduction via a heteroscedastic extension of LDA: the Chernoff criterion
    Marco Loog
    Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
    IEEE Trans Pattern Anal Mach Intell 26:732-9. 2004
    ..This criterion combines separation information present in the class mean as well as the class covariance matrices. Extensive experiments and a comparison with similar dimension reduction techniques are presented...
  6. ncbi request reprint Segmentation of anatomical structures in chest radiographs using supervised methods: a comparative study on a public database
    Bram van Ginneken
    Image Sciences Institute, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
    Med Image Anal 10:19-40. 2006
    ..All results, including the manual segmentations, have been made publicly available to facilitate future comparative studies...
  7. doi request reprint On combining computer-aided detection systems
    Meindert Niemeijer
    University Medical Center Utrecht, Image Sciences Institute, 3584 CX Utrecht, The Netherlands
    IEEE Trans Med Imaging 30:215-23. 2011
    ..For both applications, combination results in a large and significant increase in performance when compared to the best individual CAD system...
  8. ncbi request reprint A family of principal component analyses for dealing with outliers
    J Eugenio Iglesias
    Department of Computer Science, University of Copenhagen, Denmark
    Med Image Comput Comput Assist Interv 10:178-85. 2007
    ..The results show that the algorithm can implement both an outlier-enhancing and a robust PCA. The former improves the segmentation performance in fractured vertebrae, while the latter does so in the unfractured ones...
  9. doi request reprint On distributional assumptions and whitened cosine similarities
    Marco Loog
    Pattern Recognition Group, Faculty of Elctrical Engineering, Mathematics and Computer Science, Delft Unversity of Technology, Delf, The Netherlands
    IEEE Trans Pattern Anal Mach Intell 30:1114-5. 2008
    ..29, no. 6, pp. 1086-1090, June 2007. This communication makes the observation that some of the distributional assumptions made to derive this measure are very restrictive and, considered simultaneously, even inconsistent...
  10. ncbi request reprint Localized maximum entropy shape modelling
    Marco Loog
    Department of Computer Science, Nordic Bioscience A S, University of Copenhagen, Herlev, Copenhagen, Denmark
    Inf Process Med Imaging 20:619-29. 2007
    ..The experiments on point distributions demonstrate that improved shape models can be obtained using this localized maximum entropy modelling...
  11. doi request reprint Automated effect-specific mammographic pattern measures
    Jakob Raundahl
    Department of Computer Science DIKU, University of Copenhagen, 2100 Copenhagen, Denmark
    IEEE Trans Med Imaging 27:1054-60. 2008
    ..Age effects are significantly detected by our method where standard methodologies fail. The separation of HRT subpopulations using our approach is comparable to the best methodology, which is interactive...
  12. doi request reprint Efficient segmentation by sparse pixel classification
    Erik B Dam
    Nordic Bioscience, 2730 Herlev, Denmark
    IEEE Trans Med Imaging 27:1525-34. 2008
    ..We show that each algorithm is optimal for specific tasks, and that both algorithms allow a speedup of one or more orders of magnitude on typical segmentation tasks...
  13. ncbi request reprint Quantifying effect-specific mammographic density
    Jakob Raundahl
    University of Copenhagen, Department of Computer Science, Denmark
    Med Image Comput Comput Assist Interv 10:580-7. 2007
    ..Moreover, the automated method is capable of detecting age effects where standard methodologies completely fail...