Improving Deformable Image Registration Accuracy through a Hybrid Similarity Metric and CycleGAN Based Auto-Segmentation.

Purpose: Deformable image registration (DIR) plays a critical role in adaptive radiation therapy (ART) to accommodate anatomical changes. However, conventional intensity-based DIR methods face challenges when registering images with unequal image intensities. In these cases, DIR accuracy can be improved using a hybrid image similarity metric which matches both image intensities and the location of known structures.

Discussing Weight with Patients in Primary Care in Australia: A Mixed Methods Experimental Study.

Background: Weight bias is characterised by negative attitudes towards people with a higher weight and is widespread in healthcare. Primary care professionals sometimes avoid discussing weight with patients due to concerns about upsetting them, insufficient training, resources, or referral pathways. There is, however, a responsibility for primary care professionals to address the health needs of patients, which may require discussing weight.

Developing an educational resource for people experiencing eating disorders during the menopause transition: A qualitative co-design study.

Background: The pronounced changes in reproductive hormones, such as oestradiol and progesterone, that occur during the menopause transition can contribute to increased risk of eating disorder onset or exacerbate a pre-existing eating disorder. Despite this heightened risk, there is a lack of available education and support that takes into consideration the unique challenges of experiencing an eating disorder during the menopause transition. This research aimed to qualitatively explore the perspectives of people with a lived experience of an eating disorder during the menopause transition, and to co-design a support option that addressed their unmet needs.

Challenges in using data on fathers/partners to study prenatal exposures and offspring health.

Paternal exposures (and other non-maternal factors) around pregnancy could have important effects on offspring health. One challenge is that data on partners are usually from a subgroup of mothers with data, potentially introducing selection bias, limiting generalisability of findings. We aimed to investigate the potential for selection bias in studies using partner data.