The Medical Image Segmentation Tool Set (iSEG) is a fully integrated segmentation (including pre- and postprocessing) toolbox for the efficient, fast, and flexible generation of anatomical models from various types of imaging data. A wide selection of segmentation methods, including competitive region growing approaches, fuzzy connectedness analysis, level-set methods, topologically flexible interpolation, and dedicated vasculature segmentation, ensures the efficient and flexible generation of surface models.
Co-visualization of image data and segmented regions.
iSEG features a unique set of novel flexibly combinable (semi-) automatic and interactive segmentation algorithms, e.g., to optimize the generation of models with many different tissues. Anatomical reference atlases are also available.
Capable of handling a variety of image data (CT, MRI) and large-scale models.
iSEG offers unique possibilities for medical diagnosis/ treatment and basic research applications, e.g., for personalized modeling and treatment planning, or to investigate physical and physiological processes in realistic anatomical environments.
Slice view during MRI data segmentation.
Visualization of image data and DTI-based fiber tracking to facilitate the realistic placement of neuron models.
Overlay of MR imaging data and segmented bones and organs of an anatomical model.