Context-aware Volume Modeling of Skeletal Muscles

Abstract

This paper presents an interactive volume modeling method that constructs skeletal muscles from an existing volumetric dataset. Our approach provides users with an intuitive modeling interface and produces compelling results that conform to the characteristic anatomy in the input volume. The algorithmic core of our method is an intuitive anatomy classification approach, suited to accommodate spatial constraints on the muscle volume. The presented work is useful in illustrative visualization, volumetric information fusion and volume illustration that involve muscle modeling, where the spatial context should be faithfully preserved.