Enhancement of breathing simulation using individual lobe segmentation

• Main Authors: Lertrusdachakul Intuon, Leni Pierre-Emmanuel, Gschwind Regine
• Format: Article
• Language: English
• Published: EDP Sciences 2016-01-01
• Series: EPJ Web of Conferences
• Online Access: http://dx.doi.org/10.1051/epjconf/201612400005

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.