Tissue Segmentation of Brain MRI

被引：0

作者：

Dvorak, Pavel ^{[1
,2
]}

Bartusek, Karel ^{[2
]}

Mikulka, Jan ^{[3
]}

机构：

[1] Brno Univ Technol, Fac Elect Engn & Commun, Dept Telecommun, Brno 61200, Czech Republic

[2] ASCR Vvi, Inst Sci Instruments, Brno 61264, Czech Republic

[3] Brno Univ Technol, Fac Elect Engn & Commun, Dept Theoret & Expt Elect, Brno 61200, Czech Republic

来源：

2015 38TH INTERNATIONAL CONFERENCE ON TELECOMMUNICATIONS AND SIGNAL PROCESSING (TSP) | 2015年

关键词：

Brain; Gaussian Mixture Model; GMM; Image segmentation; Magnetic Resonance;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This work focuses on segmentation of magnetic resonance images of brain. The segmentation is based on assumption that in magnetic resonance images with high signal-to-noise ratio, the noise can be approximated by Gaussian. The method is tested on stand-alone simulated 2D MR images of healthy brain. The comparison between T1-weighted, T2-weighted and multi parametric images is performed. The proposed algorithm is used to segment brain images into three different tissues. For the proposed method, the best results were achieved for stand-alone T1-weighted images, while stand-alone T2-weighted images show the worst results. The achieved results slightly vary for particular tissue.

引用

页码：735 / 738

页数：4

共 17 条

[1] [Anonymous], PROGR ELECTROMAGNETI
[2] Cocosco C. A., 1997, NeuroImage
[3] CORTES C, 1995, MACH LEARN, V20, P273, DOI 10.1023/A:1022627411411
[4] MEASURES OF THE AMOUNT OF ECOLOGIC ASSOCIATION BETWEEN SPECIES
DICE, LR
[J]. ECOLOGY, 1945, 26 (03) : 297 - 302
[5] Dvorak P, 2013, 2013 36TH INTERNATIONAL CONFERENCE ON TELECOMMUNICATIONS AND SIGNAL PROCESSING (TSP), P577, DOI 10.1109/TSP.2013.6614000
[6] A novel fuzzy Dempster-Shafer inference system for brain MRI segmentation
Ghasemi, J.
Ghaderi, R.
Mollaei, M. R. Karami
Hojjatoleslami, S. A.
[J]. INFORMATION SCIENCES, 2013, 223 : 205 - 220
[7] Magnetic Resonance Imaging of Surgical Implants Made from Weak Magnetic Materials
Gogola, D.
Krafcik, A.
Strbak, O.
Frollo, I.
[J]. MEASUREMENT SCIENCE REVIEW, 2013, 13 (04): : 165 - 168
[8] THE RICIAN DISTRIBUTION OF NOISY MRI DATA
GUDBJARTSSON, H
PATZ, S
[J]. MAGNETIC RESONANCE IN MEDICINE, 1995, 34 (06) : 910 - 914
[9] Automatic segmentation of brain MRI in high-dimensional local and non-local feature space based on sparse representation
Khalilzadeh, Mohammad Mandi
Fatemizadeh, Emad
Behnam, Hamid
[J]. MAGNETIC RESONANCE IMAGING, 2013, 31 (05) : 733 - 741
[10] Macqueen J., 1967, P 5 BERKELEY S MATH, VVolume 233, P281, DOI DOI 10.1007/S11665-016-2173-6

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