INSTITUTE OF AUTOMATION; CHINESE ACADEMY OF SCIENCES
发明人:
FAN, YONG,LI, HONGMING
申请号：
CNCN2011/084340
公开号：
WO2013/091186A1
申请日:
2011.12.21
申请国别(地区):
WO
年份:
2013
代理人:
摘要：
An automatic brain tumor segmentation method for a multi-parametric 3D magnetic resonance image, including: classifying each voxel in an image and acquiring the probability that the image belongs to a brain tumor area extracting multi-scale structure information about the image constructing a multi-scale brain tumor probability image based on an initial brain tumor probability image and the multi-scale structure information about the image determining a significant tumor area based on the multi-scale brain tumor probability image acquiring a robust initial tumor segmentation tag based on tumor probability information about an initial image and the significant tumor area and using a tag propagation method based on the graph theory to separate the brain tumor area. The present invention acquires robust initial tumor segmentation tag information which is reliable in statistics, compact in space and has enough voxels, which is advantageous for the accuracy and reliability of the tumor segmentation result. The segmentation method based on tag propagation reduces the influence on the segmentation result by inter-individual image grayscale difference and insufficient training statistics information to a certain extent, improving the stability of tumor segmentation.Linvention concerne un procédé de segmentation automatique de tumeur cérébrale dans des images de résonance magnétique 3D multi-paramètre, consistant à classer chaque voxel dune image et à sassurer que limage appartient probablement à une zone de tumeur cérébrale à extraire des informations de structure multi-échelle relatives à limage à construire une image de probabilité de tumeur cérébrale multi-échelle en fonction dune image de probabilité de tumeur cérébrale initiale et dinformations de structure multi-échelle relatives à limage à déterminer une zone de tumeur significative en fonction de limage de probabilité de tumeur cérébrale multi-échelle à acquérir une étiquette de segmentation de tumeur initiale r
