DocumentCode
2972660
Title
A new fast Chinese Visible Human brain skull stripping method
Author
Yunjie, Chen ; Jianwei, Zhang ; Shunfeng, Wang
Author_Institution
Dept. of Math, Nanjing Univ. of Inf. Sci. & Technol., Nanjing, China
fYear
2009
fDate
22-24 June 2009
Firstpage
1104
Lastpage
1109
Abstract
Image data of the entire cadaver from the Chinese visible human is being used to produce three-dimensional images and software for humanhuman anatomy research. The anatomy of human brain is more complicated. The Chinese Visible Human data was serially sectioned at 0.2 mm intervals without anything perfused. Each sectioned surface was inputted into a personal computer to produce anatomical images. With the effect of noise, bias field, and fake grey matters, it is a challenging task to build a digital three dimensional representation of a human brain. In order to obtain more accurate representation, the brain regions must be separated from highly variable background regions to obtain a suitable stack of segmentation images. We use adapted Gauss Mixture model as a promising starting point for a sophisticated segmentation framework of color images within 3-dimensions. The model can classify images meanwhile estimate the bias field. For the effect of the fake grey matters, a proper image preprocessing strategy turned out to be necessary for accurate and robust segmentation results. We present a complete high resolution and accurate segmentation of the CVH brain. Based on these images, 3D representation is presented.
Keywords
brain; image colour analysis; image representation; image segmentation; medical image processing; Chinese visible human brain skull stripping method; adapted Gauss Mixture model; brain representation; fake grey matters; image segmentation; uman anatomy research; Anatomy; Cadaver; Color; Educational technology; Gaussian processes; Humans; Image reconstruction; Image segmentation; Information science; Skull;
fLanguage
English
Publisher
ieee
Conference_Titel
Information and Automation, 2009. ICIA '09. International Conference on
Conference_Location
Zhuhai, Macau
Print_ISBN
978-1-4244-3607-1
Electronic_ISBN
978-1-4244-3608-8
Type
conf
DOI
10.1109/ICINFA.2009.5205082
Filename
5205082
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