Coregistration of multimodal diagnostic images is crucial for qualitative and quantitative multiparametric analysis. While\nretrospective coregistration is computationally intense and could be inaccurate, hybrid PET/MR scanners allow acquiring\nimplicitly coregistered images. Aim of this study is to assess the performance of state-of-the-art coregistration methods applied\nto PET and MR acquired as single modalities, comparing the results with the implicitly coregistration of a hybrid PET/MR, in\ncomplex anatomical regions such as head/neck (HN). A dataset consisting of PET/CT and PET/MR subsequently acquired in\ntwenty-three patients was considered: performance of rigid (RR) and deformable (DR) registration obtained by a commercial\nsoftware and an open-source registration package was evaluated. Registration accuracy was qualitatively assessed in terms of\nvisual alignment of anatomical structures and qualitatively measured by the Dice scores computed on segmented tumors in PET\nand MRI. The resulting scores highlighted that hybrid PET/MR showed higher registration accuracy than retrospectively\ncoregistered images, because of an overall misalignment after RR, unrealistic deformations and volume variations after DR.\nDR revealed superior performance compared to RR due to complex nonrigid movements of HN district. Moreover,\nsimultaneous PET/MR offers unique datasets serving as ground truth for the improvement and validation of coregistration\nalgorithms, if acquired with PET/CT.
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