As an input to 3meD software a variable number of sections representing any part of human body is supplied; this sections can have different types of resolution and they may be more or less numerous. The software can manage a huge amount of images, enabling user to a bidimensional view of them over three planes (axial, sagittal, coronal).
The application software makes images study simple and straightforward, providing images meta information and agile but effective tools for a three-dimensional model creation, evaluation and export as close as possible to the real counterpart.
Human body organs three-dimensional detailed rebuilding necessarily requires parts of interest identification, so of the organs themselves. In fact, it is not possible to reconstruct an object without knowing the edges that delimit it in the space.
Clustering algorithms family who accomplish this task within n-dimensional images is represented by segmentation algorithms. Segmentation consists of splitting an image in a set of regions, such that each region represents an area of significant interest for a particular application domain which the algorithm is suited for.
Our solution implements some specifically segmentation algorithms designed for several oncological contexts and less specific algorithms for general purpose, which allow user to identify generic areas of interest that have similar characteristics, such as bones or organs.