This paper describes general aspects of an automated expert system for Lymph Node Hemopathology, which utilizes methods of segmentation and classification for performing image prototype similarity matching (IPSM). The expert system consists of a set of representative prototype images of a large number of histologic features required to differentiate different lymph node pathologies. A query case, which may consist of one or more images, is compared against each prototype set and is assigned a degree of similarity by calculating a distance metric in a multidimensional feature space. Introductory motivation to this problem is presented together with technical details of the low-level segmentation algorithms utilized. As a representative application, results are presented for cases, which are dominated by cytologic characteristics.