Interstitial fibrosis and morphologic changes in kidney glomeruli, the structural effects of many diseases, lead to significant pathologic alterations. A reliable and objective method to accurately quantify the extent of interstitial fibrosis and the degree of alteration in glomerular morphology is needed for both clinical practice and experimental work. The morphometric methods of quantification described to date are time-consuming and require trained personnel. This article describes the design and validation of an image analysis-based application (Fibrosis HR) for automatically and rapidly quantifying interstitial fibrosis and glomerular morphology in the same tissue section stained with Sirius red. The image processing algorithms described herein automatically segment interstitial fibrosis and mesangial matrix using automatic thresholding and morphologic filtering. The glomerular region is extracted by a simple interactive step and an automatic mathematical morphology algorithm, whereas the glomerular tuft is automatically segmented with automatic thresholding and a sequence of Boolean and mathematical morphology operations. All extracted areas are automatically quantified in absolute (microm2) and relative (%) values. For validation of this method, interstitial fibrosis, mesangial matrix, and glomerular and glomerular tuft areas were manually segmented and their quantifications statistically compared with those obtained automatically. Statistical analyses showed significant intra- and interoperator variability in manual segmentation of interstitial fibrosis, mesangial matrix, and glomerular tuft areas. Automatic quantifications of the same areas did not differ significantly from their mean manual evaluations. There was no significant intra- or interoperator variability in the interactive identification of the glomerular region. In conclusion, Fibrosis HR produces robust, fully reproducible, accurate, objective, and reliable quantifications, which facilitate the evaluation of in vivo experimental models of renal interstitial and glomerular pathologies and improve the accuracy of clinicopathologic analyses of renal diseases in human biopsies.