Fully Automatic Segmentation of Gross Target Volume and Organs-at-Risk for Radiotherapy Planning of Nasopharyngeal Carcinoma

Understand

Target segmentation in CT images of Head&Neck (H&N) region is challenging due to low contrast between adjacent soft tissue.

• The SegRap 2023 challenge has been focused on benchmarking the segmentation algorithms of Nasopharyngeal Carcinoma (NPC) which would be employed as auto-contouring tools for radiation treatment planning purposes.
• We propose a fully-automatic framework and develop two models for a) segmentation of 45 Organs at Risk (OARs) and b) two Gross Tumor Volumes (GTVs).
• To this end, we preprocess the image volumes by harmonizing the intensity distributions and then automatically cropping the volumes around the target regions.