Deep learning –based multimodal segmentation of oropharyngeal squamous cell carcinoma on CT and MRI using self-configuring nnU-Net

ConclusionThe self-configuring nnU-Net demonstrated reliable and accurate segmentation of OPSCC on CT and MRI. The multimodal CT-MR model showed promising results for the simultaneous segmentation on CT and MRI.Clinical relevance statementDeep learning –based automatic detection and segmentation of oropharyngeal squamous cell carcinoma on pre-treatment CT and MRI would facilitate radiologic response assessment and radiotherapy planning.Key Points•The nnU-Net framework produced a reliable and accurate segmentation of OPSCC on CT and MRI.•MR and CT-MR models showed higher DSC and lower Hausdorff distance than the CT model.•Correlation coefficients between the ground truth and predicted segmentation volumes were high in all the three models.
Source: European Radiology - Category: Radiology Source Type: research