Histopathological analysis of cellular changes in the stroked brain provides critical information pertaining to inflammation, cell death, glial scarring, and other dynamic injury and recovery responses. However, commonly used manual approaches are hindered by limitations in speed, accuracy, bias, and the breadth of morphological information that can be obtained. Here, a semi-automated high-content imaging (HCI) and CellProfiler histological analysis method was developed and used in pig model of ischemic stroke to overcome these limitations. This unbiased, semi-automated analysis approach revealed regional and cell specific morphological signatures of immune and neural cells post-stroke. These features can in turn provide information of disease pathogenesis and evolution with high resolution, as well as be used in therapeutic screening applications.