Reconstruction of the Cerebral Ventricles using Several Segmentation Methods based on Level Set Implemented by Insight Toolkit (ITK)

The segmentation of cerebral structures in medical images has numerous clinical applications. It can provide significant aids for the diagnosis of some pathology. In this work, we developed a software application for the segmentation of medical images using a new segmentation method based on the theory of deformable models. We use the advantages of the levitra 10mg uk zyrtec specialized mathematical libraries, such as ITK (Insight Tool Kit) for the processing, https://www.acheterviagrafr24.com/viagra-online/ segmenta-tion and registration of images, we develop a specialized interface implemented on FLTK able to extract the information and the user’s knowledge for transfer it to the segmentations methods of ITK. This new methodology is based on proc-essing chain that includes the following steps: 1) Load the image. 2) Select one of the five segmentation method: Fast marching, Geodesic Contours Activate, Laplacian, Threshold with Level Set and Shape detection implemented on ITK for the “Level Set” technique. 3) Adjust the parameters for each method. 4) Select a seed, which determines the region of interest. And finally 5) the segmented 2D image is obtained. The new contribution of this work consists on providing of a new software application using a new interface for the segmentation and 3D visualization of the segmented models. In conclusion, this segmentation procedure is faster than the manual segmentation, with the advantage that it allows to use the same patient as anatomical reference, which has more precision than a generic atlas.

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