NR AUOA
AU Linguraru,M.G.; Ayache,N.; Gonzalez Ballester,M.A.; Bardinet,E.; Galanaud,D.; Haik,S.; Faucheux,B.; Cozzone,P.J.; Dormont,D.; Brandel,J.P.
TI New ratios for the detection and classification of CJD in multisequence MRI of the brain
QU Medical Image Computing and Computer-assisted Intervention : MICCAI - International Conference on Medical Image Computing and Computer-Assisted Intervention 2005; 8(2): 492-9
PT evaluation studies; journal article; validation studies
AB We present a method for the analysis of deep grey brain nuclei for accurate detection of human spongiform encephalopathy in multisequence MRI of the brain. We employ T1, T2 and FLAIR-T2 MR sequences for the detection of intensity deviations in the internal nuclei. The MR data are registered to a probabilistic atlas and normalised in intensity prior to the segmentation of hyperintensities using a foveal model. Anatomical data from a segmented atlas are employed to refine the registration and remove false positives. The results are robust over the patient data and in accordance to the clinical ground truth. Our method further allows the quantification of intensity distributions in basal ganglia. sCJD patient FLAIR images are classified with a more significant hypersignal in caudate nuclei (10/10) and putamen (6/10) than in thalami. Defining normalised MRI measures of the intensity relations between the internal grey nuclei of patients, we robustly differentiate sCJD and variant CJD (vCJD) patients, as an attempt towards the automatic detection and classification of human spongiform encephalopathies.
MH Algorithms; Artificial Intelligence; Brain/*pathology; Brain Mapping/*methods; Cluster Analysis; Creutzfeldt-Jakob Syndrome/*classification/*diagnosis; Humans; Image Enhancement/methods; Image Interpretation, Computer-Assisted/*methods; Imaging, Three-Dimensional/methods; Magnetic Resonance Imaging/*methods; Pattern Recognition, Automated/*methods; Reproducibility of Results; Research Support, Non-U.S. Gov't; Sensitivity and Specificity; Severity of Illness Index; Subtraction Technique
AD Marius George Linguraru, Nicholas Ayache, Miguel Angel González Ballester, Epidaure/Asclepios Research Group - INRIA, 06902 Sophia Antipolis Cedex, France; Marius George Linguraru (mglin@deas.harvard.edu), Department of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138 USA; Eric Bardinet, Didier Dormont, CNRS UPR640-LENA, 75651 Paris, France; Miguel Angel González Ballester, MEM-ISTB, University of Bern, CH-3014 Bern, Switzerland; Damien Galanaud, Department of Neuroradiology, La Pitié-Salpêtrière Hospital, 75013 Paris, France; Damien Galanaud, Patrick Cozzone, CRMBM UMR CNRS 6612, Faculty of Medicine, 13005 Marseille, France; Stéphane Haïk, Baptiste Faucheux, Jean-Philippe Brandel, INSERM U360, La Pitié-Salpêtrière Hospital, 75651 Paris, France; Stéphane Haïk, Baptiste Faucheux, R. Escourolle Neuropathological Laboratory, La Pitié-Salpêtrière Hospital, 75651 Paris, France; Stéphane Haïk, Jean-Philippe Brandel, The National Reference Cell of CJD, La Pitié-Salpêtrière Hospital, 75651 Paris, France
SP englisch
PO Deutschland