[Automatic extraction and segmentation of the intracranial structure from cerebral computed tomography].
This paper describes a new method for extracting and segmenting intracranial structure from serial images of cerebral computerized tomography automatically. A region growing- and morphology-based approach was first developed to extract intracranial structures from the serial images of cerebral computerized tomography, and focusing on the problems of parameter initialization of the expectation maximization (EM) algorithm, an improved EM algorithm based on parameter- limited GMM was presented to segment the intracranial structures successfully. Experimental results of the algorithm showed that this method was effective for all cerebral computerized tomography images from bottom to top of the cerebrum.
Jiang
Shao-feng
SF
Key Lab for Medical Image Processing, Southern Medical University, Guangzhou 510515, China.
Chen
Wu-fan
WF
Feng
Qian-jin
QJ
Yang
Su-hua
SH
D000465:Algorithms; D054022:Cerebrum / Q000000981:diagnostic imaging*; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D014057:Tomography, X-Ray Computed