Automatic landmark extraction from a class of hands using growing neural gas

A new method for automatically building statistical shape models from a set of training examples and in particular from a class of hands. In this method, landmark extraction is achieved using a self-organising neural network, the Growing Neural Gas (GNG), which is used to preserve the topology of any input space. Using GNG, the topological relations of a given set of deformable shapes can be learned. We describe how shape models can be built automatically by posing the correspondence problem on the behaviour of self-organising networks that are capable of adapting their topology to an input manifold, and due to their dynamic character to readapt it to the shape of the objects. Results are given for the training set of hand outlines, showing that the proposed method preserves accurate models

Automated Analysis of Corpora Callosa

Abstract. This report describes and evaluates the steps needed to perform modern model-based interpretation of the corpus callosum in MRI. The process is discussed from the initial landmark-free contours to fullfledged statistical models based on the Active Appearance Models framework. Topics treated include landmark placement, background modelling and multi-resolution analysis. Preliminary quantitative and qualitative validation in a cross-sectional study show that fully automated analysis and segmentation of the corpus callosum are feasible.

Correspondence evaluation in local shape analysis and structural subdivision

journal articleRegional volumetric and local shape analysis has become of increasing interest to the neuroimaging community due to the potential to locate morphological changes. In this paper we compare three common correspondence methods applied to two studies of hippocampal shape in schizophrenia: correspondence via deformable registration, spherical harmonics (SPHARM) and Minimum Description Length (MDL) optimization. These correspondence methods are evaluated in respect to local statistical shape analysis and structural subdivision analysis. Results show a non-negligible influence of the choice of correspondence especially in studies with low numbers of subjects. The differences are especially striking in the structural subdivision analysis and hints at a possible source for the diverging findings in many subdivision studies. Our comparative study is not meant to be exhaustive, but rather raises awareness of the issue and shows that assessing the validity of the correspondence is an important step