Enhancement of breathing simulation using individual lobe segmentation
IRMA/CE Laboratory, UMR CNRS 6249, Université Bourgogne Franche-Comté, 4 place Tharradin 25200 MONTBELIARD, France
Published online: 21 September 2016
To tackle thorax movement from CT images, we have developed a platform to simulate a customized breathing cycle, where the pulmonary movement has been considered only at the rough border of the whole lung by artificial neural networks (ANN). The goal of this work is to include additional information of the lung lobe. Thus, more ANN will be used and future simulation will be able to take into consideration the impact of tumor on lobe movement. We present a new automatic segmentation algorithm that enables the extraction of lobar contour data using sliding mask and direction estimation. These improvements enhance the overall system performance in which higher precision and more accurate treatments can be expected.
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.