Neuroimaging teams tested shorter PET acquisition for tau assessment, reporting that five-minute fluorine-18-MK6240 PET scans on high-sensitivity PET/MR systems preserved diagnostic accuracy and quantitative tau readouts in patients with cognitive impairment. The work targets a key bottleneck in amyloid/tau workflows—time and throughput. In oncology imaging, a separate CT volumetry study using deep learning segmentation improved inter-observer consistency for pulmonary nodule assessments in screening workflows, reducing management discrepancies. Together, the findings reinforce that AI-enabled imaging quantification is increasingly being evaluated as a reliability tool—not just a prediction model.