PDE-constrained shape registration to characterize biological growth and morphogenesis from imaging data

Special Issue: Imaging-based methods in computational medicine

“…This type of method ignores the role of physics constraints and therefore can result in inaccurate mapping between geometries, as well as limiting our understanding of a given disease to fully geometric indicators, ignoring other sources of information. The work reported in Pawar et al [8] and Cox et al [2] shows how to pose registration problems constrained by PDEs describing tissue deformation. As a result, PDE-constrained registration can uncover not just geometric changes, but also strain maps, which are mechanistic inputs for models of tissue growth and remodeling.…”

“…However, IGA has emerged as a powerful alternative, particularly in image analysis applications, for its ability to represent accurate geometries while also relying on locally supported, complete, and high-continuity basis functions. In this issue, the work by [2,4,8,14] illustrate new developments in IGA methods for imaging-based biophysics models.…”

“…The musculoskeletal system is the focus of Tajdari et al [15], who created personalized models of spine growth in scoliosis, and that of Crutison and Royston [3], who obtained material parameters from different MR imaging modalities on muscles. Meanwhile, skin [8] and tumors are also studied [7,11].…”