Automatic landmark identification in 3D image volumes by topography conserving approximation of contour data

If organs are represented by a compact and non-ambiguous mathematical function, many actually interactive diagnostics on tomographic images can be performed automated. Such a representation is constructed from the organ's surface by mapping characteristic topographic structures (landmarks) onto identical function variables. Organs scanned by tomographic images series--periacetabular region of 14 hip joints imaged by X-ray CT--may be segmented. Their surface's contour points are approximated by tensor-product-B-splines (TPBSs). In a reference TPBS surface model landmarks are denoted interactively to define a mapping `variable-pair of the TPBS vs. landmark'. The patient TPBS models are mapped onto the reference model by fitting the model function values. The fit, and so the landmark identification, is performed by a homology function, which is applied to the patient model's variable plane. For simply shaped organs, the transformation of the tomographic to the topographic representation was possible using only the values and first order derivatives of the TPBSs. The presented landmark identification method avoids unnecessary assumptions of model deformation mechanism and has low computational costs.