Poster — Thur Eve — 49: Investigating the Effects of Motion on Texture within the Lung

Automated methods using CT‐image‐based texture features have shown promise for segmentation of lungtumours. Combining CT with PET features for use in segmentation has been shown to improve segmentation accuracy compared to using either modality separately and has potential for use in accurate internal target volume definition in lungcancer. One issue of particular importance in lungtumor segmentation is the effect of motion on the measures extracted from PET and CTimages. This aspect is under investigation using maximum intensity projections (MIPs) in addition to temporally gated CT, PET and un‐gated PET data sets. Preliminary results from 13 patients (9 diagnosed with lungcancer; 4 diagnosed with cancers outside the lung area, representing healthy lungtissue) show that with gated CT, PET and CT homogeneity, PET Entropy, and CT Coarseness are some of the strongest discriminators for use in classification with statistical distance measures of up to 2.0 between normal and abnormal tissue. The texture features from MIPs of 4 of the patients show that they present somewhat less discriminating feature values, as to be expected. Their usefulness within the context of segmentation remains to be investigated.