DocumentCode
526657
Title
Notice of Retraction
Automatic extraction of brain Mid-sagittal Line from normal and abnormal CT images
Author
Gang Xu ; Jing Sun
Author_Institution
Dept. of Electr. & Electron. Eng., North China Electr. Power Univ., Beijing, China
Volume
4
fYear
2010
fDate
9-11 July 2010
Firstpage
178
Lastpage
183
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
We present a detailed description of an algorithm to detect the Mid-sagittal Line (MSL) in the human brain CT. The method seeks the line with respect to the image maximum symmetry. Our method relies on the moving window to define the counterpart points between both sides of the brain with the symmetry line. The matching points are measured by the adaptive weighted mutual information based on local region. The algorithm has been tested on brain images from various imaging modalities in both normal brain CT and brain CT with a lesion. Results were evaluated and were judged to be consistently correct.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
We present a detailed description of an algorithm to detect the Mid-sagittal Line (MSL) in the human brain CT. The method seeks the line with respect to the image maximum symmetry. Our method relies on the moving window to define the counterpart points between both sides of the brain with the symmetry line. The matching points are measured by the adaptive weighted mutual information based on local region. The algorithm has been tested on brain images from various imaging modalities in both normal brain CT and brain CT with a lesion. Results were evaluated and were judged to be consistently correct.
Keywords
brain; computerised tomography; image matching; medical image processing; CT images; adaptive weighted mutual information; automatic extraction; brain mid-sagittal line; image maximum symmetry; imaging modalities; mid-sagittal line; Computed tomography; Gallium nitride; Lesions; Positron emission tomography; Sun; Brain; CT; Medical image processing; Mid-Sagittal Line; Symmetry detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-5537-9
Type
conf
DOI
10.1109/ICCSIT.2010.5564810
Filename
5564810
Link To Document