Bjoern Menze - Publications

Image-Based Physiological Modeling

We seek for new techniques in multimodal data analysis that combine physiological and physical process models together with probabilistic image observation functions. The focus is on tumor imaging and applications in clinical neuroscience.

Menze BH, Strettin E, Konukoglu E and Ayache N. Image-based modeling of tumor growth in patients with glioma. In: CS Garbe, R Rannacher, U Platt, T Wagner (eds.), Optimal control in image processing. Springer, Heidelberg. In press.
(preprint)

Menze BH, Van Leemput K, Honkela A, Konukoglu E, Weber MA, Ayache N and Golland P. A generative approach for image-based modeling of tumor growth. Proc IPMI 2011. LNCS 6801, 735-47.
(PubMed) (publisher) (preprint)

⇒ "This paper introduces a joint generative model of tumor growth and image observation. Model personalization relies on a forward model of the patho-physiological process combined with different image likelihood functions, and an efficient Bayesian inference approach."

Konukoglu E, Relan J, Cilingir U, Menze BH, Chinchapatnam P, Jadidif A, Cochet H, Hocini M, Delingette H, Jais P, Hassaguerre M, Ayache N and Sermesant M. Efficient probabilistic model personalization integrating uncertainty on data and parameters: application to Eikonal-diffusion models in cardiac electrophysiology Progress in Biophysics and Molecular Biology 2011. In press.
(PubMed) (publisher) (preprint)

Menze BH, Hamprecht FA. Multimodal medical image analysis: from visualization to disease modeling. (Front Cover, Editorial) Zeitschrift fur Medizinische Physik 2011. 1:1-2
(PubMed) (publisher)

Kelm BM, Kaster FO, Henning A, Weber MA, Bachert P, Boesiger P, Hamprecht FA and Menze BH. Using spatial prior knowledge in the spectral fitting of magnetic resonance spectroscopic images. NMR in Biomedicine 2011. In press.
(PubMed) (publisher) (preprint)

⇒ "This paper introduces a Bayesian smoothness prior in the spectral fitting of the metabolic model functions which can be used in addition to commonly employed prior knowledge in the quantification of MRS images."

Konukoglu E, Clatz O, Menze BH, Stieltjes B, Weber MA, Mandonnet E, Delinegette H and Ayache N. Image guided personalization of reaction-diffusion type tumor growth models using modified anisotropic Eikonal equations. IEEE Transactions on Medical Imaging 2010. 29:77-95
(PubMed) (publisher) (preprint)

Riklin-Raviv T, Van Leemput K, Menze BH, Wells WM and Golland P. Segmentation of image ensembles via latent atlases. Medical Image Analysis 2010. 14:654-65.
(PubMed) (publisher) (preprint)

Menze BH, Van Leemput K, Lashkari D, Weber MA, Ayache N and Golland P. A generative model for brain tumor segmentation in multi-modal images. Proc MICCAI 2010. LNCS 6362, 151-59
(PubMed) (publisher) (preprint)

⇒ "This paper introduces a generative probabilistic model for segmenting brain lesions in multi-dimensional images with different lesion boundaries in each channel, reflecting difference in tumor appearance across modalities. The model augments an atlas of healthy tissue priors with a latent atlas of the lesion."

Kelm BM, Menze BH, Nix O, Zechmann C and Hamprecht FA. Estimating kinetic parameter maps from dynamic contrast-enhanced MRI using spatial prior knowledge. IEEE Transaction on Medical Imaging 2009. 28:1534-47.
(PubMed) (publisher) (preprint)

Riklin Raviv T, Menze BH, Van Leemput K, Stieltjes B, Weber MA, Ayache N, Wells WM and Golland P. Joint segmentation via patient-specific latent anatomy model. Proc MICCAI-PMMIA 2009. 244-55
(publisher) (preprint)

Menze BH, Konukoglu E, Clatz O, Stieltjes B, Nix O, Weber MA, Kikinis R and Ayache N. Estimating the growth process of gliomas using physiological models. Proc ISMRM Workshop on Frontiers of Magnetic Resonance: From Tumor Cell to Cancer Patient. Nice, France. 2008
(publisher)

Kelm BM, Müller N, Menze BH and Hamprecht FA. Bayesian estimation of smooth parameter maps for dynamic contrast-enhanced magnetic resonance images with block-ICM. Proc CVPR-MMBIA 2006. 96-103
(publisher) (preprint)

Medical Computer Vision and Pattern Recognition

We seek for new pattern recognition approaches for detection tasks, localization tasks, and classification tasks in medical image analysis and biomedical testing. A methodological focus is on techniques derived from the random forest framework.

Zechmann CM, Menze BH, Kelm BM, Zamecnik P, Ikinger U, Waldherr R, Delorme S, Hamprecht FA, Bachert P. Automated vs. manual pattern recognition of 3D 1H MRSI data of patients with prostate cancer. Academic Radiology 2012. In press.

Menze BH, Kelm BM, Splitthoff DN, Koethe U, Hamprecht F. On oblique random forests. Proc ECML PKDD 2011. LNCS 6912, 453-469.
(publisher) (preprint) (R Package) (Videolecture)

⇒ "This paper proposes to employ 'oblique' split directions at internal nodes of the trees using linear discriminative models, rather than using random coefficients or univariate splits as in the original random forest."

Geremia E, Clatz O, Menze BH, Konukoglu E, Criminisi A and Ayache N. Spatial decision forests for MS lesion segmentation in multi-channel magnetic resonance images. Neuroimage 2011. In press.
(PubMed) (publisher) (preprint)

Langs G, Menze BH, Lashkari D and Golland P. Detecting stable distributed patterns of brain activation in fMRI using Gini contrast. Neuroimage 2011. In press.
(PubMed) (publisher) (preprint)

Menze BH, Langs G, Tu Z and Criminisi A (eds.). Medical Computer Vision: Recognition techniques and applications in medical imaging. Proceedings of the MICCAI 2010 Workshop on Medical Computer Vision (MCV 2010). Lecture Notes in Computer Science 6533. Springer Publishing, Heidelberg. 2011.
(publisher) (workshop)

Geremia E, Menze BH, Clatz O, Konukoglu E, Criminisi A and Ayache N. Spatial decision forests for MS lesion segmentation in multi-channel magnetic resonance images. Proc MICCAI 2010. LNCS 6362, 664-772
(PubMed) (preprint)

Kaster FO, Menze BH, Weber MA and Hamprecht FA. Comparative validation of graphical models for learning tumor segmentations from noisy manual annotations. Proc MICCAI-MCV 2010. LNCS 6533, 84-94
(publisher) (preprint)

Menze BH, Kelm BM, Masuch R, Himmelreich U, Bachert P, Petrich W and Hamprecht FA. A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data. BMC Bioinformatics 2009. 10: 213.
(PubMed) (publisher, open access)

Koenig T, Menze BH, Kirchner M, Monigatti F, Parker KC, Patterson T, Jebanathirajah Steen JA, Hamprecht FA and Steen H. Robust Prediction of the MASCOT score for an improved quality assessment in mass spectrometric proteomics. Journal of Proteome Research 2008. 7: 3708-17.
(PubMed) (publisher) (preprint)

Menze BH, Kelm BM, Weber MA, Bachert P and Hamprecht FA. Mimicking the human expert: pattern recognition for an automated assessment of data quality in magnetic resonance spectroscopic images. Magnetic Resonance in Medicine 2008. 59: 1457-66.
(PubMed) (publisher) (preprint)

Gorlitz L*, Menze BH*, Weber MA, Kelm BM and Hamprecht FA. Semi-supervised tumor detection in magnetic resonance spectroscopic images using discriminative random fields. (* contributed equally) Proc DAGM 2007. LNCS 4713, 224-33
(publisher) (preprint)

Menze BH, Petrich W and Hamprecht FA. Multivariate feature selection and hierarchical classification for infrared spectroscopy: serum-based detection of bovine spongiform encephalopathy. Analytical and Bioanalytical Chemistry 2007. 387: 801-1807
(PubMed) (publisher) (preprint)

Kelm BM, Menze BH, Zechmann CM, Baudendistel KT and Hamprecht FA. Automated estimation of tumor probability in prostate magnetic resonance spectroscopic imaging: pattern recognition vs. quantification. Magnetic Resonance in Medicine 2007. 57: 150-159
(PubMed) (publisher) (preprint)

Menze BH, Lichy MP, Bachert P, Kelm BM, Schlemmer HP and Hamprecht FA. Optimal classification of long echo time in vivo magnetic resonance spectra in the detection of recurrent brain tumors. NMR in Biomedicine 2006. 19: 599-60
(PubMed) (publisher) (preprint)

Archaeological Remote Sensing

This work aims at developing quantitative methods for archaeological prospection in the Near East using remote sensing techniques at a large scale.

Menze BH and Ur JA. Multi-temporal classification of multi-spectral images: settlement survey in northeastern Syria at a large scale In: DC Comer, MJ Harrower (eds.), Space Archaeology: Mapping Ancient Landscapes with Air and Spaceborne Imagery. Springer, New York. Forthcoming.

Menze BH and Ur JA. Mapping patterns of long-term settlement in Northern Mesopotamia at a large scale. Proceedings of the National Academy of Science of the United States 2012. In press
(PubMed) (publisher) (preprint) (data repository)

⇒ "This paper establishes a comprehensive record of ancient settlement sites in the Khabur Basin, north-eastern Syria, representing the largest systematic satellite-imagery-based survey in archaeology."

Selected press coverage: Nature, BBC, CNN, ABC, Huffington Post, Dailymail, The Atlantic, Discovery, Discover Magazine, Smithsonian, io9, Mashable (Video), NPR (Radio), Der Standard, Focus, Spiegel Online, Harvard Gazette

Menze BH and Ur JA. Detection of early settlements in the central Tigris region by classifying multi-spectral satellite imagery. In: P Miglus (ed.), Between the Cultures: The Central Tigris Region in Mesopotamia from the 3rd to the 1st Millennium BC, Heidelberger Studien zum Alten Orient 12. Heidelberger Orientverlag, Heidelberg, Germany. 2011.

Menze BH and Ur JA. Classification of multispectral ASTER imagery in the archaeological survey for settlement sites of the Near East. In: ME Schaepman et al. (eds.), Proc 10th Intern Symp on Physical Measurements and Signature in Remote Sensing (ISPMSRS 07), Davos, Switzerland. Intern Arch of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. 36. 2007 244-249
(publisher) (preprint)

Menze BH, Mühl S, Sherratt AG. Virtual survey on north Mesopotamian tell sites by means of satellite remote sensing. In: B Ooghe, G Verhoeven (eds.), Broadening horizons: Multidisciplinary Approaches to Landscape Study. Cambridge Scholars Publishing, Newcastle upon Tyne, UK. 2007 5-29
(publisher) (preprint)

Menze BH, Kelm BM and Hamprecht FA. From Eigenspots to Fisherspots: Latent spaces in the nonlinear detection of spot patterns in a highly variable background. In: HJ Lenz, R Decker (eds.), Advances in Data Analysis., vol. 33 of Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Heidelberg and Berlin. 2007 255-262
(publisher) (preprint)

Menze BH, Ur JA and Sherratt AG. Detection of ancient settlement mounds: Archaeological survey based on the SRTM terrain model. Photogrammetric Engineering and Remote Sensing 2006. 72: 321-327
(publisher, open access)

Menze BH, Ur JA and Sherratt AG. Tell Spotting - surveying Near Eastern settlement mounds from space. In: S Dequal (ed.), Proc 20th CIPA International Symposium (CIPA 05), Torino, Italy. 2005 458-462
(publisher) (preprint)

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