Magnetic resonance (MR) imaging is an imaging modality that is used in the management and diagnosis of acute stroke. Common MR imaging techniques such as diffusion weighted imaging (DWI) and apparent diffusion coefficient maps (ADC) are used routinely in the diagnosis of acute infarcts. However, advances in radiology information systems and imaging protocols have led to an overload of image information that can be difficult to manage and time consuming. Automated techniques to assist in the identification of acute ischemic stroke can prove beneficial to 1) the physician by providing a mechanism for early detection and 2) the patient by providing effective stroke therapy at an early stage. We have processed DW images and ADC maps using a novel automated Relative Difference Map (RDM) method that was tailored to the identification and delineation of the stroke region. Results indicate that the technique can delineate regions of acute infarctions on DW images and ADC maps. A formal evaluation of the RDM algorithm was performed by comparing accuracy measurements between 1) expert generated ground truths with the RDM delineated DWI infarcts and 2) RDM delineated DWI infarcts with RDM delineated ADC infarcts. The accuracy measurements indicate that the RDM delineated DWI infarcts are comparable to the expert generated ground truths. The true positive volume fraction value (TPVF), between RDM delineated DWI and ADC infarcts, is nonzero for all cases with an acute infarct while the value for non-acute cases remains zero.