A new postprocessing method is described for CT detection of acute middle cerebral artery (MCA) territory infarcts by histograph analysis of density values. The density values in each CT slice were histographically recorded for each hemisphere. A density-difference diagram was calculated by digital subtraction of the histogram of the left hemisphere from that of the right. Pixels within the highest density-difference ranges were highlighted. To investigate the value of this method CT studies of 30 patients with acute MCA territory infarcts and of 15 normal CT studies were analysed by two radiologists and neurosurgeons. CT images with and without postprocessing were assessed for the presence, site and size of infarcts. Follow-up CTwas used as control. With density-difference analysis (DDA) the detection rate for infarcts increased significantly (96 % compared to 61 %). In no case was a correct diagnosis made on the unpostprocessed images falsely revised with DDA. All normal CT studies were detected correctly using DDA.