Computational Anatomy (CA) is emerging as a discipline focused on the quantitative analysis of variability of biological shape.  Although the study of biological shapes can be traced to the beginnings of modern science, in his influential treatise "On Growth and Form'' in 1917, D'Arcy Thompson had the clearest vision of what lay ahead, in which shapes are modeled as an orbit under groups of mathematical shape transformations.  

Research in Computational Anatomy in the ICM is focused on development and application of CA methods in two major areas – analysis of the structure function of the human brain and heart and its variation in health and disease. 

Applications of CA in brain science have developed rapidly, with applications of large deformation brain mapping technologies that provide mechanisms for discovering neuropsychiatric disorders of many types. As one example, the hippocampus is a region in the brain that has been implicated in schizophrenia and other neurodegenerative diseases such as Alzheimer’s. Using large deformation brain mapping tools, researchers can define, visualize, and measure the volume and shape of the hippocampus. These methods have enabled precise assessment of changes in hippocampal formation and have been used to demonstrate that hippocampal volume and shape changes derived from computational anatomy large deformation brain mapping tools may be useful in distinguishing early dementia of the Alzheimer type from healthy aging.

Applications of CA methods to the analysis of heart structure/function have are currently addressing three problems: (i) construction and labeling of the anatomical submanifolds of the heart as curves, surfaces and subvolumes; (ii) comparison of the anatomical manifolds via estimation of the underlying diffeomorphic correspondences defining the shape or geometry of the anatomical manifolds; and (iii) generation of probabilistic laws of anatomical variation on the images for inference and disease testing within the anatomical models. These CA methods are being used to analyze the nature of cardiac shape, fiber and laminar structure remodeling in heart disease. 

See also the Center for Imaging Science (CIS)