Automatic liver segmentation method based on deformation model of CT image

The invention discloses an automatic liver segmentation method based on a deformation model of a CT image. The method comprises the steps: 1, building a liver atlas, and representing the deformation model SRDM based on sparsity, and the liver atlas comprises a gray level image and a marking image corresponding to the gray level image; 2, performing liver map registration on a to-be-segmented target image, and constructing a non-rigid transformation model for aligning a grayscale image of the liver map to the target image; 3, regularizing the non-rigid transformation model in the step 2 by using a sparse representation deformation model SRDM; 4, propagating the labeled image of the liver map to a target image by using the regularized transformation model to obtain an initial segmentation result; and step 5, for the data with relatively large segmentation errors, carrying out fine segmentation on an initial segmentation result. Through the scheme, the segmentation precision close to thatof a semi-automatic segm