Official websites use. Share sensitive information only on official, secure websites. Given sufficient training samples, statistical shape models can provide detailed population representations for use in anthropological and computational genetic studies, injury biomechanics, musculoskeletal disease models or implant design optimization. While the technique has become extremely popular for the description of isolated anatomical structures, it suffers from positional interference when applied to coupled or articulated input data.
In the present manuscript we describe and validate a novel approach to extract positional noise from such coupled data. The technique was first validated and then implemented in a multicomponent model of the lower limb. The impact of noise on the model itself as well as on the description of sexual dimorphism was evaluated.
The novelty of our methodology lies in the fact that no rigid transformations are calculated or imposed on the data by means of idealized joint definitions and by extension the models obtained from them. Differences in pose at the time of image acquisition adds rotational noise to articulated components in multicomponent shape models. A PLS regression was used to learn the relation between isolated osteological structures and their alignment within the full lower limb.
Excluding positional variance, increases model compactness and improves correlations with other associated biological variables such as sex. Statistical shape models SSM have been established as a robust tool for segmentation of medical images and for the description of variation in anatomy Almeida et al.
In particular, the models allow for accurate parameterization of complex data such as an individual's anatomical phenotype as well as for the realistic description of the distribution of anatomy in the population, by use of conventional multivariate statistics on dense sets of homologous landmarks representing the shape of the underlying structures Audenaert, ; Heimann and Meinzer, Given sufficient training samples, they can approximate almost any naturally occurring configurations, permitting extended usage and advancements in numerous scientific areas including anthropology, evolutionary biology, forensics, implant design, anatomy, epidemiology and last but not least clinics, for the distinction of physiological versus pathological anatomical variation.
