Automatic MRI meningioma segmentation using estimation maximization

Yi Fen Tsai, I-Jen Chiang, Yeng Chi Lee, Chun Chih Liao, Kao Lung Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Pages3074-3077
Number of pages4
Volume7 VOLS
Publication statusPublished - 2005
Event2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 - Shanghai, China
Duration: Sep 1 2005Sep 4 2005

Other

Other2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
CountryChina
CityShanghai
Period9/1/059/4/05

Fingerprint

Magnetic resonance imaging
Neurosurgery
Tumors
Brain
Image processing
Imaging techniques
Planning

ASJC Scopus subject areas

  • Bioengineering

Cite this

Tsai, Y. F., Chiang, I-J., Lee, Y. C., Liao, C. C., & Wang, K. L. (2005). Automatic MRI meningioma segmentation using estimation maximization. In Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings (Vol. 7 VOLS, pp. 3074-3077). [1617124]

Automatic MRI meningioma segmentation using estimation maximization. / Tsai, Yi Fen; Chiang, I-Jen; Lee, Yeng Chi; Liao, Chun Chih; Wang, Kao Lung.

Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. Vol. 7 VOLS 2005. p. 3074-3077 1617124.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Tsai, YF, Chiang, I-J, Lee, YC, Liao, CC & Wang, KL 2005, Automatic MRI meningioma segmentation using estimation maximization. in Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. vol. 7 VOLS, 1617124, pp. 3074-3077, 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005, Shanghai, China, 9/1/05.
Tsai YF, Chiang I-J, Lee YC, Liao CC, Wang KL. Automatic MRI meningioma segmentation using estimation maximization. In Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. Vol. 7 VOLS. 2005. p. 3074-3077. 1617124
Tsai, Yi Fen ; Chiang, I-Jen ; Lee, Yeng Chi ; Liao, Chun Chih ; Wang, Kao Lung. / Automatic MRI meningioma segmentation using estimation maximization. Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. Vol. 7 VOLS 2005. pp. 3074-3077
@inproceedings{86198747aaef4f5d8145b2ed4077c617,
title = "Automatic MRI meningioma segmentation using estimation maximization",
abstract = "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.",
author = "Tsai, {Yi Fen} and I-Jen Chiang and Lee, {Yeng Chi} and Liao, {Chun Chih} and Wang, {Kao Lung}",
year = "2005",
language = "English",
isbn = "0780387406",
volume = "7 VOLS",
pages = "3074--3077",
booktitle = "Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings",

}

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.

UR - http://www.scopus.com/inward/record.url?scp=33846912796&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33846912796&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:33846912796

SN - 0780387406

SN - 9780780387409

VL - 7 VOLS

SP - 3074

EP - 3077

BT - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

ER -