Self-supervised parametric map estimation for multiplexed PET with a deep image prior.

Multiplexed positron emission tomography (mPET) imaging allows simultaneous observation of physiological and pathological information from multiple tracers in a single PET scan. Although supervised deep learning has demonstrated superior performance in mPET image separation compared to purely model-based methods, acquiring large amounts of paired single-tracer data and multi-tracer data for training poses a practical challenge and needs extended scan durations for patients. In addition, the generalisation ability of the supervised learning framework is a concern, as the patient being scanned and their tracer kinetics may potentially fall outside the training distribution.

Modelling the health labour market outlook in Kenya: Supply, needs and investment requirements for health workers, 2021-2035.

Kenya is committed to achieving Universal Health Coverage (UHC) within its devolved health system in which significant investments have been made in health infrastructure, workforce development, and service delivery. Despite these efforts, the country faces considerable health workforce challenges. To address these, the Ministry of Health undertook a comprehensive Health Labour Market Analysis (HLMA) in 2022 to generate evidence supporting the development of responsive health workforce policies.

Initial results of the Hyperion IIPET insert for simultaneous PET-MRI applied to atherosclerotic plaque imaging in New-Zealand white rabbits.

In preclinical research, in vivo imaging of mice and rats is more common than any other animal species, since their physiopathology is very well- known and many genetically altered disease models exist. Animal studies based on small rodents are usually performed using dedicated preclinical imaging systems with high spatial resolution. For studies that require animal models such as mini- pigs or New-Zealand White (NZW) rabbits, imaging systems with larger bore sizes are required.

Deep learned triple-tracer multiplexed PET myocardial image separation.

Introduction: In multiplexed positron emission tomography (mPET) imaging, physiological and pathological information from different radiotracers can be observed simultaneously in a single dynamic PET scan. The separation of mPET signals within a single PET scan is challenging due to the fact that the PET scanner measures the sum of the PET signals of all the tracers. The conventional multi-tracer compartment modeling (MTCM) method requires staggered injections and assumes that the arterial input functions (AIFs) of each tracer are known.

Bronchoconstriction with inhaled ATP in healthy volunteers.

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