The volume of the skull defect should be one of the most important quantitative measures for decompressive craniectomy. However, there has been no study focusing on automated estimation of the volume from postoperative computed tomography (CT). This study develops and validates three methods that can automatically locate, recover and measure the missing skull region based on symmetry without preoperative images. The low resolution estimate (LRE) method involves downsizing CT images,¯nding the axis of symmetry for each slice, and estimating the location and size of the missing skull regions. The intact mid-sagittal plane (i MSP) can be de¯ned either by dimension-bydimension (DBD) method as a global symmetry plane or by Liu's method as a regression from each slices. The skull defect volume can then be calculated by skull volume di®erence (SVD) with respect to each i MSP. During a 48-month period between July 2006 and June 2010 at a regional hospital in northern Taiwan, we collected 30 sets of nonvolumetric CT images after craniectomies. Three board-certi¯ed neurosurgeons perform computer-assisted volumetric analysis of skull defect volume V Man as the gold standard for evaluating the performance of our algorithm. We compare the error of the three volumetry methods. The error of V LRE is smaller than that of V Liu (p < 0:0001) and V DBD (p ¼ 0:034). The error of V DBD is signi¯cant smaller than that of V Liu (p ¼ 0:001). The correlation coe±cients between V Man and V LRE , V Liu , V DBD are 0.98, 0.88 and 0.95, respectively. In conclusion, these methods can help to de¯ne the skull defect volume in postoperative images and provide information of the immediate volume gain after decompressive craniectomies. The i MSP of the postoperative skull can be reliably identi¯ed using the DBD method.