At the same time 3D printers, traditionally used in industrial applications, are now available for home use thanks to low-cost desktop alternatives. This has made it possible to generate anatomical models using a standard personal computer with little prior anatomical knowledge. Recent advances in segmentation software have made it increasingly easy to automatically or semi-automatically extract the surface of structures of interest from three-dimensional (3D) medical imaging data. MRI offers excellent soft tissue contrast, which, for example, enables differentiation between white and grey matter in the brain.

The modality thus lends itself well to segmenting structures such as bones (high density) or lungs (low density).

CT pixel intensities directly correlate to tissue density. Depending on the imaging modality, different features can be observed and different image segmentation algorithms will be appropriate. CT and MRI are widely used to image biological features, ranging from whole-body imaging to particular areas of interest such as tumours or specific parts of the brain. Imaging phantoms are also important for the development of novel imaging modalities such as photoacoustics, or for validation of image-based biomarkers such as pore size estimation using nuclear magnetic resonance, where they provide controlled experimental environments.Īnatomically accurate models can be computer-generated from medical image data. Lastly, anatomical phantoms can be designed to mimic tissue when imaged with the modality of interest most commonly ultrasound, Computed Tomography (CT), or Magnetic Resonance Imaging (MRI). In addition, the phantoms can be used for pre-operative surgical planning, which has been shown to be beneficial in craniofacial surgery and is being explored in a number of other surgical fields. For example, improvement of central venous catheter insertions has been achieved by the use of anatomically and ultrasonically accurate teaching phantoms. Simulation-based training with anatomical models reduces the risks of surgical interventions, which are directly linked to patient experience and healthcare costs.

In the clinic, the physical interaction with models facilitates learning anatomy and how different structures interact spatially in the body. Anatomical models have applications in clinical training and surgical planning as well as in medical imaging research.

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