An advanced prototyping process for highly accurate models in biomedical applications
An integrated prototyping process for the derivation of complex medical models is introduced. The use of medical models can support today’s medicine by improving diagnosis and surgical planning, teaching and patient information. To withstand the challenges of time and accuracy, a process for generating accurate virtual and physical medical models is needed. The introduced process offers the possibility to derive virtual and physical models for biomedical engineering applications. Reviewing the current situation of medical virtual prototyping and rapid prototyping applications, limitations were found related to the influential variables of data acquisition, data processing, virtual reality use, and rapid prototyping manufacturing. An integrated prototyping concept (MPP) is introduced for embedding virtual prototyping and rapid prototyping in biomedical applications. Data processing and 3D modeling of complex anatomical structures from computerized image data were investigated and discussed in detail. Finally, parameter analyses were evaluated to derive optimal parameters needed for preparing 3D models for virtual prototyping and rapid prototyping processing in medicine. Summarizing from the accuracy analysis, the present investigation is the first to examine tomographic scanning as decisive factor for inaccuracy of medical prototyping models. The human nose is an example of a complex anatomical geometry, which has been an object of scientific research interest for several years. One of the applications introduced here uses the developed MPP concept as basis for a procedure that generates animated medical models in a virtual reality environment. Although, attempts are being made to reconstruct the human nose as an experimental rapid prototyping model, a process for accurate reconstruction as a transparent rapid prototyping model is still missing. The MPP concept allows fabricating individual models of the human nose with a high level of accuracy and transparency. Finally, temporal analysis revealed major time improvements in modeling complex anatomical models compared to approaches without optimized process sequences and approved parameters. The prototyping of the human hip was the second example used. The results of this particular example emphasized the strengths of the medial prototyping process in preparing hip models for presurgery planning. Here, accuracy was enhanced considerably. Rapid prototyping hip models can provide assistance as a surgical planning tool in complex cases, especially in improving surgical results and implant stability. Thus, the accuracy and time of model generation is improved, thereby establishing a defined process for medical model generation. Considering the novel findings of broad improvements in accuracy and time, a new field of research is emerging, serving both virtual surgery applications and physical implant generation. The MPP developed in this work can be viewed as an initial approach for launching international standards of prototyping technologies in medicine.