Jung, FlorianFlorianJungSteger, SebastianSebastianStegerKnapp, OliverOliverKnappNoll, MatthiasMatthiasNollWesarg, StefanStefanWesarg2022-03-122022-03-122014https://publica.fraunhofer.de/handle/publica/38752610.1007/978-3-319-13909-8_4Radiation therapy plays a major role in head and neck cancer treatment. Segmentation of organs at risk prior to the radiation therapy helps to prevent the radiation beam from damaging healthy tissue, whereas a concentrated ray can target the cancerous regions. Unfortunately, the manual annotation of all relevant structures in the head and neck area is very time-consuming and existing atlas-based solutions dont provide sufficient segmentation accuracy. Therefore, we propose an coupled shape model (CoSMo) for the segmentation of key structures within the head and neck area. The models adaptation to a test image is done with respect to the appearance of its items and the trained articulation space. 40 data sets labeled by clinicians containing 22 structures were used to build the CoSMo. Even on very challenging data sets with unnatural postures, which occur far more often than expected, the model adaptation algorithm succeeds. A first evaluation showed an average directed Hausdorff distance of 13.22mm and an average DICE overlap of 0.62. Furthermore, we review some of the challenges we encountered during the course of building our model from image data, taken from actual radiation therapy planing cases.enautomatic segmentationstatistical shape model (SSM)radiation therapyBusiness Field: Visual decision supportResearch Line: Human computer interaction (HCI)conference paper