TY - GEN
T1 - Automatic MRI meningioma segmentation using estimation maximization
AU - Tsai, Yi Fen
AU - Chiang, I-Jen
AU - Lee, Yeng Chi
AU - Liao, Chun Chih
AU - Wang, Kao Lung
PY - 2005
Y1 - 2005
N2 - With the advancement of the imaging facility and image processing technique, computer assisted surgical planning and image guided technology have become increasingly used in neurosurgery. For MRI has the characteristic of multi-spectral image data., so knowledge-base techniques is widely used in brain MRI segmentation. Here we recognize the location of the tumor automatically and provide an accurate result by Estimation Maximization method. Simultaneously, promote the efficiency of reading image as well.
AB - With the advancement of the imaging facility and image processing technique, computer assisted surgical planning and image guided technology have become increasingly used in neurosurgery. For MRI has the characteristic of multi-spectral image data., so knowledge-base techniques is widely used in brain MRI segmentation. Here we recognize the location of the tumor automatically and provide an accurate result by Estimation Maximization method. Simultaneously, promote the efficiency of reading image as well.
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UR - http://www.scopus.com/inward/citedby.url?scp=33846912796&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:33846912796
SN - 0780387406
SN - 9780780387409
T3 - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
SP - 3074
EP - 3077
BT - Proceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
T2 - 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
Y2 - 1 September 2005 through 4 September 2005
ER -