2.4. 3D reconstruction of CT images

First, to have a better 3D reconstruction, we directly extracted the DICOM files raw data from the imaging modality console. Then, we anonymized the extracted 2D DICOM images using Matlab software, in order to ensure the hospital's best privacy to the patient.

To open these files and have a better 3D reconstruction's quality on the TableEDU 4.0 software, we deleted the corrupted files. Then, an adapted data processing was done on a personal computer, before transferring the DICOM files to the Anatomage table [19, 20, 21, 22, 23, 24].

At last, a 3D reconstruction algorithm was used on the TableEDU 4.0 software, as shown in the flowchart bellow (Figure 1). It enabled users to display a dissectible 3D volume on the Anatomage table's screen. The 3D reconstructions are obtained using image segmentation and contour detection provided automatically by the TableEDU 4.0 software of the Anatomage table. This allows to stack images with the same gray scale. The obtained clusters represent a 3D volume that can be adjusted using different filters of the software. The 3D volume can be modified using different tools such as the volume visibility control tool and the contrast slider tool.

Flowchart of the 3D reconstruction realization.