Landré Jérôme, Lebonvallet Stéphane, Ruan Su, Xiaobing Li, Tianshuang Qui, Brunotte François
CReSTIC, IUT de Troyes, Troyes, France.
Annu Int Conf IEEE Eng Med Biol Soc. 2008;2008:3130-3. doi: 10.1109/IEMBS.2008.4649867.
This paper presents a tumor detecting system that allows interactive 3D tumor visualization and tumor volume measurements. An improved level set method is proposed to automatically segment the tumor images slice by slice. PET images are used to detect the tumor while CT images make a 3D representation of the patient's body possible. An initial slice with a seed within the tumor is firstly chosen by the operator. The system then performs automatically the tumor volume segmentation that allows the clinician to visualize the tumor, to measure it and to evaluate the best medical treatment adapted to the patient.
