A digital pediatric brain structure atlas from T1-weighted MR images

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4191 LNCS - II, Issue , 2006, Pages 332-339

  Shan, Zuyao Y ^a   Parra, Carlos ^b   Ji, Qing ^a   Ogg, Robert J ^a   Zhang, Yong ^a   Laningham, Fred H ^a   Reddick, Wilburn E ^a,b  

^a ST JUDE CHILDREN S RESEARCH HOSPITAL   (United States)

^b University of Memphis   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN; FEATURE EXTRACTION; IMAGE SEGMENTATION; MAGNETIC RESONANCE IMAGING; MATHEMATICAL MODELS; PATIENT MONITORING;

PEDIATRIC BRAIN STRUCTURE; STRUCTURAL MESH MODELS; SURFACE CURVATURE;

BIOMEDICAL ENGINEERING;

ALGORITHM; ANATOMY; ARTICLE; ARTIFICIAL INTELLIGENCE; AUDIOVISUAL EQUIPMENT; AUTOMATED PATTERN RECOGNITION; BRAIN; CHILD; COMPUTER ASSISTED DIAGNOSIS; COMPUTER GRAPHICS; EVALUATION; FEMALE; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; MEDICAL ILLUSTRATION; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ANATOMY, ARTISTIC; ARTIFICIAL INTELLIGENCE; BRAIN; CHILD; COMPUTER GRAPHICS; FEMALE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; MEDICAL ILLUSTRATION; MODELS, ANATOMIC; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED; SUBTRACTION TECHNIQUE;

EID: 79551687585     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11866763_41     Document Type: Conference Paper

References (15)

1. Ganser K.A., Dickhaus H., Metzner R., et al: A deformable digital brain atlas system according to Talairach and Tournoux. Medical Image Analysis 8 (2004) 3-22
2. Pommert A., Riemer M., Schiemann T., et al: Knowledge-Based and 3D Imaging-Systems in Medical-Education. Information Processing '94, Vol II IFIP Trans A-Computer Sci. and Tech. 52 (1994) 525-532
3. Kikinis R., Shenton M.E., Iosifescu D.V., et al: A digital brain atlas for surgical planning, model-driven segmentation, and teaching. IEEE Tran. Visualization and Computer Graphics 2 (1996) 232-241
4. Thurfjell L., Bohm C., Bengtsson E.: Cba - An Atlas-Based Software Tool Used to Facilitate the Interpretation of Neuroimaging Data. Computer Methods and Programs in Biomedicine 47 (1995) 51-71
5. Tzourio-Mazoyer N., Landeau B., Papathanassiou D., et al: Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 15 (2002) 273-289
6. Paus T., Zijdenbos A., Worsley K., et al: Structural maturation of neural pathways in children and adolescents: In vivo study. Science 283 (1999) 1908-1911
7. Wilke M., Schmithorst V.J., Holland S.K.: Normative pediatric brain data for spatial normalization and segmentation differs from standard adult data. Magnetic Resonance in Medicine 50 (2003) 749-757
8. Kates W.R., Warsofsky I.S., Patwardhan A., et al: Automated Talairach atlas-based parcellation and measurement of cerebral lobes in children. Psychiatry Research-Neuroimaging 91 (1999) 11-30
9. Maes F., Collignon A., Vandermeulen D., et al: Multimodality image registration by maximization of mutual information. IEEE Trans. Med. Imaging 16 (1997) 187-198
10. nd Ed. New York CAMBRIDGE UNIVERSITY PRESS (1992)
11. rd Ed. Baltimore, MD Williams & Wilkins (1985)
12. Kim J.J., Crespo-Facorro B., Andreasen N.C., et al: An MRI-based parcellation method for the temporal lobe. Neuroimage 11 (2000) 271-288
13. Crespo-Facorro B., Kim J.J., Andreasen N.C., et al: Human frontal cortex: An MRI-based parcellation method. Neuroimage 10 (1999) 500-519
14. nd rev. ed. Berlin, Germany Springer-Verlag (2000)
15. Shan Z.Y., Parra C., Ji Q., Jain J., Reddick W.E. A Knowledge-Guided Active Model Method of Cortical Structure Segmentation on Pediatric MR images. J Magn Reson Imging, In Press.