Purpose In order to improve segmentation accuracy in head and neck cancer (HNC) radiotherapy treatment planning for the 1.5T MR-Linac, 3D fat-suppressed T2-weighted MRI sequences were developed and optimized. Methods After initial testing of fat suppression techniques, SPectral Attenuated Inversion Recovery (SPAIR) was chosen as the fat suppression technique. Five candidate SPAIR sequences and a non-suppressed T2-weighted sequence were acquired on five HNC patients on the Unity MR-Linac. The primary tumor, metastatic lymph nodes, parotid glands, and pterygoid muscles were delineated by five segmentors. A robust image quality analysis platform was developed to objectively score the SPAIR sequences based on a combination of qualitative and quantitative metrics. Results Sequences were analyzed for signal-to-noise (SNR), contrast-to-noise (CNR) compared to fat and muscle, conspicuity, pairwise distance metrics, segmentor assessment, and MR physicist assessment. From this analysis, the non-suppressed sequence was inferior to each of the SPAIR sequences for the primary tumor, lymph nodes, and parotid glands, but was superior for the pterygoid muscles. Two SPAIR sequences consistently received the highest scores among the analysis categories and are recommended for use to Unity MR-Linac users for HNC radiotherapy treatment planning. Conclusions Two deliverables resulted from this study. First, an optimized 3D fat-suppressed T2-weighted sequence was developed that can be disseminated to Unity MR-Linac users. Second, a robust image quality analysis process pathway, used to objectively score the various SPAIR sequences, was developed and can be customized and generalized to any image quality optimization. Improved segmentation accuracy with the proposed SPAIR sequence can potentially lead to improved treatment outcomes and reduced toxicity by maximizing target coverage and minimizing organ-at-risk exposure.