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Related Literatures

Related Literatures
C.H. Lee, S.W. Wang, A. Murtha, M.R.G. Brown, and R. Greiner, "Segmenting Brain Tumors using Pseudo-Conditional Random Fields." MICCAI, 2008.
M. Wels, G. Carneiro, A. Aplas, M. Huber, J. Hornegger, and D. Comaniciu, "A Discriminative Model-Constrained Graph Cuts Approach to Fully Automated Pediatric Brain Tumor Segmentation in 3-D MRI." MICCAI, 2008.
I. Nwogu, J. Corso, "Exploratory Identification of Image-Based Biomarkers for Solid Mass Pulmonary Tumors." MICCAI, 2008.
Z. Tu, "Probabilistic Boosting-Tree: Learning Discriminant Models for Classification, Recognition, and Clustering." 2006.
L. Teverovskiy, and Y. Liu, "Truly 3D Midsagittal Plane Extraction for Robust Neuroimage Registration." Biomedical Imaging: Macro to Nano, 2006.
M. Prastawa, E. Bullitt, G. Gerig, "Synthetic Ground Truth for Validation of Brain Tumor MRI Segmentation." 2005.
M. Prastawa, E. Bullitt, G. Gerig, "A Brain Tumor Segmentation Framework Base On Outlier Detection." Medical Image Analysis, Vol 150, 2004.
Y. Liu, R. Collins, W. Rothfus, "Robust Midsagittal Plane Extraction rom Normal and Pathological 3-D Neuroradiology Images." Medical Imaging, Vol 20, No. 3, pp. 175-192, 2001.
Y. Liu, R. Collin, W. Rothfus, "Automatic Extraction of the Central Symmetry (Mid-Sagittal) Plane from Neuroradiology Images." CMU-RI-TR-96-40, 1996.
L. Grady, "Random Walks for Image Segmentation." IEEE Transactions of Pattern Analysis and Machine Intelligence, Vol. 28, No. 11, Nov . 2006.
K.M. Iftekharuddin, J. Zheng, M.A. Islam, and R.J. Ogg, "Fractal-based brain tumor detection in multimodal MRI." Applied Mathematics and Computation, 2008.
S. Kumar, and M. Hebert, "Discriminative Random Fields.", International Journal of Computer vision, Vol. 68, No. 2, pp. 179-201, June 2006.
C.H. Lee, A. Murtha, A. Bistritz, J. Sander, and R. Greiner, "Segmenting Brain Tumors with Conditional Random Fields and Support Vector Machines." Computer Vision for Biomedical Image Applications, Vol. 3765, pp. 469-478, Nov. 2005.
D. Huttenlocher, G. A. Klanderman, and W. Rucklidge, "Comparing Images Using the Hausdorff Distance." IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 15, No. 9, Sep. 1993.
D. Cobzas, N. Birkbeck, M. Schmidt, M. Jagersand, A. Murtha, "3D Variational Brain Tumor Segmentation using a High Dimensional Feature Set." ICCV, 2007.
M. Kaus, S. Warfield, A. Nabavi, P. Black, F. Jolesz, R. Kikinis, "Automated segmentation of MR images of brain tumors." Radiology, Vol 218, pp. 586-591, 2001.
S. Ho, E. Bullitt, G. Gerig, "Level Set Evolution with Region Competition: Automatic 3-D Segmentation of Brain Tumors." ICPR, pp. 532-535, 2002.
S. Joshi, P. Lorenzen, G. Gerig, E. Bullitt, "Structural and radiometric asymmetry in brain images." Medical Image Analysis, Vol 7, Issue 2, pp. 155-170, 2003.
S. Taheri, S. Ong, V. Chong, "Threshold-based 3D Tumor Segmentation using Level Set (TSL)." IEEE Workshop on Applications of Computer Vision, 2007.
N. Ray, B. Saha, M. Brown, "Locating Brain Tumors from MR Imagery Using Symmetry." ACSSC, 2007.
J. Wang, Q. Li, T. Hirai, S. Katsuragawa, F. Li, K. Doi, "An Accurate Segmentation Method for Volumetry of Brain Tumor in 3D MRI." Medical Imaging, 2008.
J. Zhang, K. Ma, M. Er, V. Chong, "Tumor Segmentation From Magnetic Resonance Imaging by Learning via One-Class Support Vector Machine." IWAIT, 2004.
X. Xuan, Q. Liao, "Statistical Structure Analysis in MRI Brain Tumor Segmentation." ICIG, 2007.
R. Collins, W. Ge, "CSDD Features: Center-Surround Distribution Distance for Feature Extraction and Matching." ECCV, 2008.
H. Ling, K. Okada, "An Efficient Earth Mover's Distance Algorithm for Robust Histogram Comparison." IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 29, No. 5, 2007.
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F. Kruggel, J. Paul, and H. Gertz, "Texture-based segmentation of diffuse lesions of the brain's white matter." NeuroImage, Vol. 39:3, pp. 987-996, 2008.
M. Seghier, A. Ramlackhansingh, J. Crinion, A. Leff, and C. Price, "Lesion identification using unified segmentation-normalisation models and fuzzy clustering." NeuroImage, Vol. 41:4, pp. 1253-1266, 2008.
Y. Wu, S. Warfield, I. Tan, W. Wells III, D. Meier, R. Schijndel, F. Barkhof, and C. Guttmann, "Automated segmentation of multiple sclerosis lesion subtypes with multichannel MRI." NeuroImage, Vol. 32:3, pp. 1205-1215, 2006.
A. Stadlbauer, E. Moser, S. Gruber, R. Buslei, C. Nimsky, R. Fahlbusch, and O. Ganslandt, "Improved delineation of brain tumors: an automated method for segmentation based on pathologic changes of H-MRSI metabolites in gliomas." NeuroImage, Vol. 23:2, pp. 454-461, 2004.
P. Anbeek, K. Vincken, M. van Osch, R. Bisschops, and J. van der Grond, "Probabilistic segmentation of white matter lesions in MR imaging." NeuroImage, Vol. 21:3, pp. 1037-1044, 2004.
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