The authors present a systematic analysis of contemporary approaches to constructing and interpreting anamorphoses. They trace the development of these techniques – from early manual and analogue practices to modern density-equalising algorithms – and propose a structured typology of the principal forms of anamorphic transformations. The discussion includes an outline of the most widely used computational procedures, among them iterative and diffusion-based methods as well as emerging neural-network solutions. Some available software implementations, including modules embedded in mainstream GIS environments are also reviewed. Special attention is paid to using anamorphoses in medical-and-geographical studies, where they serve as an effective tool for visualising spatial heterogeneity in demographic and epidemiological processes. Drawing on examples such as mortality from malignant neoplasms and the spatial progression of the COVID-19 pandemic, we demonstrate a key advantage of the method: the ability to compare statistical indicators without distortion by shifting from the metric of geographic area to that of population distribution. Finally, a considerable analytical and communicative value of anamorphoses is substantiated and promising ways for its further refinement and integration into geoinformation technologies are outlined