DocumentCode :
1396718
Title :
Fully automatic identification of AC and PC landmarks on brain MRI using scene analysis
Author :
Vérard, Laurent ; Allain, Pascal ; Travère, Jean Marcel ; Baron, Jean Claude ; Bloyet, Daniel
Author_Institution :
CNRS, Caen, France
Volume :
16
Issue :
5
fYear :
1997
Firstpage :
610
Lastpage :
616
Abstract :
Describes a method for identification of brain structures from MRI data sets. The bulk of the paper concerns an automatic system for finding the anterior and posterior commissures [(AC) and (PC)] in the midsagittal plane. These landmarks are key for the definition of the Talairach space, commonly used in stereotactic neurosurgery, in the definition of common coordinate systems for the pooling of functional positron emission tomography (PET) images and for neuroanatomy studies. The process works according to a step-by-step procedure: it first analyzes the skull limits. A grey-level histogram is then calculated and allows an automated selection of thresholds. Then, the interhemispheric plane is detected. Following an advanced scene analysis in the midsagittal plane for anatomical structures, the AC and the PC are identified. Experimentally, with a set of 200 patients, the process never failed. Its performances and limits are comparable to that of neuroanatomy experts. Those results are due to a high degree of robustness at each step of the program.
Keywords :
biomedical NMR; brain; feature extraction; medical image processing; AC landmarks; PC landmarks; Talairach space definition; anatomical structures; brain MRI; common coordinate systems; fully automatic identification; functional positron emission tomography images; grey-level histogram; interhemispheric plane; magnetic resonance imaging; medical diagnostic imaging; midsagittal plane; neuroanatomy studies; scene analysis; Anatomical structure; Brain; Computed tomography; Histograms; Image analysis; Magnetic resonance imaging; Neurosurgery; Positron emission tomography; Robustness; Skull; Algorithms; Automatic Data Processing; Brain; Humans; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Neuroanatomy; Observer Variation; Pattern Recognition, Automated; Reproducibility of Results; Skull; Stereotaxic Techniques; Superior Colliculi; Tomography, Emission-Computed;
fLanguage :
English
Journal_Title :
Medical Imaging, IEEE Transactions on
Publisher :
ieee
ISSN :
0278-0062
Type :
jour
DOI :
10.1109/42.640751
Filename :
640751
Link To Document :
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