A Medical Image Auto-segmentation Algorithm in the Presence of Intensity Inhomogeneities
Yan Xin · Science Technology and Engineering · 2011
Accuracy and speed of medical image segmentation algorithm are technical requirement for clinical application.However,the medical images are always affected by noise,intensity inhomogeneities,etc,which make the segmentation algorithm is difficult to achieve the desired result.Manual segmentation can directly draw the expected boundaries on the original image,however,segmentation result is entirely depended on the anatomical knowledge and experience of dissector and the segmentation results are difficult to reproduce.In order to correct intensity inhomogeneities and avoid human involvement,combine a adaptation clustering algorithm based on intensity inhomogeneities with Active Shape Model(ASM),and propose an automatic segmentation method based on MR.The algorithm can correct gray of non-uniformity while scaning,and avoid to lost information for the origina image,and finally achieve fully automatic segmentation of image data.This method is more accurate than traditional algorithms and robust,and it can play a role in the medical image processing and analysis.