Our research is regularly featured in different news outlets including NIBIB Science Highlights, Radiology Business, Aunt Minnie, HealthImaging, Parkinson’s News Today and Applied Radiology and Imaging Wire. Some press releases below.
AI-based denoising in medical imaging may require further evaluation
Useful not pretty: How AI can improve medical imaging
Jha wins NSF CAREER award for imaging research
Spot the difference: Distinguishing real from fake in the age of synthetic images
Doctoral students earn awards at SPIE conference
Pushing the boundaries of the visible world
Imaging technique may measure absorbed dose from radiation therapy
Novel SPECT imaging method may measure absorbed dose from radiation therapy
Imaging technique may measure absorbed dose from radiation therapy
Novel SPECT imaging technique may measure absorbed dose from radiation therapy
SPECT technique might measure absorbed tissue dose from radiation therapy
Biomarkers for Parkinson’s disease sought through imaging
Best practices could help AI deployment in nuclear medicine
Evaluation of AI for medical imaging: A key requirement for clinical translation
Engineers develop new way to use low-count imaging for effective radiopharmaceutical therapy
WashU Expert: Patients want AI, doctors to work together
Dialing in Patient Attitudes: The Ethics of AI in Medical Decision-making
Personalized medicine for lung cancer gets closer look
Evaluation of AI for medical imaging: A key requirement for clinical translation
Framework for evaluating AI-based medical imaging method outlined
Jha’s NIH grant to support cancer research
Personalized medicine for lung cancer gets closer look
Jha to develop imaging methods with $1.8M NIH grant
NIBIB: Deep learning improves interpretation of tumors
From mathematical concept to a clinical tool
Doctoral student wins SNMMI grant
Statistical theory, deep learning, lead to novel approach to differentiate tumors
Physics, AI help researchers to better define tumor boundaries in imaging
Jha and collaborators develop framework to determine tumor boundaries in PET scans
Doctoral student wins SNMMI grant to study novel imaging methods