Multivariate mathematical morphology for DCE-MRI image analysis in angiogenesis studies

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[1]  S. Delorme,et al.  On impulse response functions computed from dynamic contrast-enhanced image data by algebraic deconvolution and compartmental modeling. , 2012, Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics.

[2]  F Lazeyras,et al.  FAST sequences optimization for contrast media pharmacokinetic quantification in tissue , 2001, Journal of magnetic resonance imaging : JMRI.

[3]  R. Cattell.  The Scree Test For The Number Of Factors. , 1966, Multivariate behavioral research.

[4]  Jesús Angulo,et al.  Filtering, segmentation and region classification by hyperspectral mathematical morphology of DCE-MRI series for angiogenesis imaging , 2008, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[5]  D M Shames,et al.  Mammary carcinoma model: correlation of macromolecular contrast-enhanced MR imaging characterizations of tumor microvasculature and histologic capillary density. , 1996, Radiology.

[6]  P. Switzer,et al.  A transformation for ordering multispectral data in terms of image quality with implications for noise removal , 1988 .

[7]  Jesús Angulo,et al.  Random Germs and Stochastic Watershed for Unsupervised Multispectral Image Segmentation , 2007, KES.

[8]  Yu Ding,et al.  Application of the Karhunen–Loeve transform temporal image filter to reduce noise in real-time cardiac cine MRI , 2009, Physics in medicine and biology.

[9]  D. Ruppert.  The Elements of Statistical Learning: Data Mining, Inference, and Prediction , 2004 .

[10]  Fernand Meyer,et al.  Levelings, Image Simplification Filters for Segmentation , 2004, Journal of Mathematical Imaging and Vision.

[11]  D L Buckley,et al.  Tracer kinetic modelling in MRI: estimating perfusion and capillary permeability , 2012, Physics in medicine and biology.

[12]  A. Jackson,et al.  Quantitative imaging biomarkers in the clinical development of targeted therapeutics: current and future perspectives. , 2008, The Lancet. Oncology.

[13]  Allan Hanbury,et al.  Morphological operators on the unit circle , 2001, IEEE Trans. Image Process..

[14]  S. Beucher.  Use of watersheds in contour detection , 1979 .

[15]  Frédérique Frouin,et al.  New criteria for assessing fit quality in dynamic contrast‐enhanced T1‐weighted MRI for perfusion and permeability imaging , 2005, Magnetic resonance in medicine.

[16]  Evis Sala,et al.  Dynamic contrast-enhanced MRI as a predictor of tumour response to radiotherapy. , 2007, The Lancet. Oncology.

[17]  Jesús Angulo,et al.  Classification-driven stochastic watershed. Application to multispectral segmentation , 2008, CGIV/MCS.

[18]  H. Kaiser.  The Application of Electronic Computers to Factor Analysis , 1960 .

[19]  Guillaume Noyel,et al.  Regionalized Random Germs by a Classification for Probabilistic Watershed Application: Angiogenesis Imaging Segmentation , 2010 .

[20]  H. Huisman,et al.  Imaging vascular function for early stage clinical trials using dynamic contrast-enhanced magnetic resonance imaging , 2012, European Radiology.

[21]  David A. Landgrebe,et al.  Hyperspectral image data analysis , 2002, IEEE Signal Process. Mag..

[22]  Guillaume Noyel.  Filtrage, réduction de dimension, classification et segmentation morphologique hyperspectrale , 2008 .

[23]  G. F. Hughes,et al.  On the mean accuracy of statistical pattern recognizers , 1968, IEEE Trans. Inf. Theory.

[24]  Yu Ding,et al.  A method to assess spatially variant noise in dynamic MR image series , 2010, Magnetic resonance in medicine.

[25]  Frédéric Y Bois,et al.  Evaluation of antiangiogenic treatment effects on tumors' microcirculation by Bayesian physiological pharmacokinetic modeling and magnetic resonance imaging. , 2006, Magnetic resonance imaging.

[26]  Kristel Michielsen,et al.  Morphological image analysis , 2000 .

[27]  Nadjia Kachenoura,et al.  Signal-to-noise ratio improvement in dynamic contrast-enhanced CT and MR imaging with automated principal component analysis filtering. , 2011, Radiology.

[28]  Fernand Meyer,et al.  An Overview of Morphological Segmentation , 2001, Int. J. Pattern Recognit. Artif. Intell..

[29]  Johannes R. Sveinsson,et al.  Classification of hyperspectral data from urban areas based on extended morphological profiles , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[30]  Jesús Angulo,et al.  On distances, paths and connections for hyperspectral image segmentation , 2007, ISMM.

[31]  J. A. Hartigan,et al.  A k-means clustering algorithm , 1979 .

[32]  Dominique Jeulin,et al.  Stochastic watershed segmentation , 2007, ISMM.

[33]  A R Padhani,et al.  In vivo monitoring of tumor angiogenesis with MR imaging. , 2000, Academic radiology.

[34]  Jesús Angulo,et al.  A new spatio-spectral morphological segmentation for multi-spectral remote-sensing images , 2010, ArXiv.

[35]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[36]  Paul Scheunders,et al.  A multivalued image wavelet representation based on multiscale fundamental forms , 2002, IEEE Trans. Image Process..

[37]  F Frouin,et al.  Reduced capillary perfusion and permeability in human tumour xenografts treated with the VEGF signalling inhibitor ZD4190: an in vivo assessment using dynamic MR imaging and macromolecular contrast media. , 2003, Magnetic resonance imaging.