Document Detail

New ratios for the detection and classification of CJD in multisequence MRI of the brain.
MedLine Citation:
PMID:  16685996     Owner:  NLM     Status:  MEDLINE    
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.
Marius George Linguraru; Nicholas Ayache; Miguel Angel González Ballester; Eric Bardinet; Damien Galanaud; Stéphane Haïk; Baptiste Faucheux; Patrick Cozzone; Didier Dormont; Jean-Philippe Brandel
Related Documents :
21111976 - Mr imaging features of common variant spinal anatomy.
14581006 - Mri of neonatal encephalopathy.
16685996 - New ratios for the detection and classification of cjd in multisequence mri of the brain.
7436466 - Visual deterioration as presentation of subacute sclerosing panencephalitis.
17566696 - Quantification of left ventricular volumes and function in patients with cardiomyopathi...
17707606 - Application of a new combined guiding technique in rf ablation of subphrenic liver tumors.
Publication Detail:
Type:  Evaluation Studies; Journal Article; Research Support, Non-U.S. Gov't; Validation Studies    
Journal Detail:
Title:  Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention     Volume:  8     ISSN:  -     ISO Abbreviation:  Med Image Comput Comput Assist Interv     Publication Date:  2005  
Date Detail:
Created Date:  2006-05-11     Completed Date:  2006-06-06     Revised Date:  2009-12-11    
Medline Journal Info:
Nlm Unique ID:  101249582     Medline TA:  Med Image Comput Comput Assist Interv     Country:  Germany    
Other Details:
Languages:  eng     Pagination:  492-9     Citation Subset:  IM    
EPIDAURE Research Group, INRIA Sophia Antipolis, France.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Artificial Intelligence
Brain / pathology*
Brain Mapping / methods*
Cluster Analysis
Creutzfeldt-Jakob Syndrome / classification*,  diagnosis*
Image Enhancement / methods
Image Interpretation, Computer-Assisted / methods*
Imaging, Three-Dimensional / methods
Magnetic Resonance Imaging / methods*
Pattern Recognition, Automated / methods*
Reproducibility of Results
Sensitivity and Specificity
Severity of Illness Index
Subtraction Technique

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

Previous Document:  Topology correction using fast marching methods and its application to brain segmentation.
Next Document:  Statistical representation and simulation of high-dimensional deformations: application to synthesiz...