This paper describes a modeller for building 3D anatomic atlases. The main contribution is the ability to incrementally learn inter-patient variations in structure, shape, and function; with support for variations in structure (topology) being of particular significance. The modeller uses graph theory as a mathematical base and is, in fact, quite general with possible applications in wider computer vision contexts. In this paper we describe the general modeller, and illustrate it specifically by showing how to use it to build a catalogue of vasculature and variations. We have used such a catalogue of vasculature for 3D reconstruction of x-ray angiograms, simulation of x-ray angiography, and interpretation of images and text combined; the first two of these are the most mature and are briefly outlined. We conclude by discussing the limitations of the model both generally and specifically.
"Modeling interpatient variation in structure, shape, and function", Proc. SPIE 3338, Medical Imaging 1998: Image Processing, (24 June 1998); doi: 10.1117/12.310925; https://doi.org/10.1117/12.310925