ABSTRACT: Liver cancer is one of the most prevalent and lethal forms of cancer, making early detection crucial for effective treatment. This paper introduces a novel approach for automated liver tumor ...
A study led by UC San Francisco and UC Davis has concluded that radiation from medical imaging is associated with a higher risk of blood cancers in children. The researchers examined data from nearly ...
Assessing the risk of radiation-induced hematologic cancer from medical imaging in children and adolescents might support informed decisions on the use of imaging. We followed a retrospective cohort ...
Abstract: This paper addresses the challenge of enhancing medical imaging analysis on edge devices while maintaining patient privacy and security. In this paper, we present a novel federated ...
This study aims to explore an autoencoder-based method for generating brain MRI images of patients with Autism Spectrum Disorder (ASD) and non-ASD individuals, and to discriminate ASD based on the ...
A new hand-held scanner can generate highly detailed 3D photoacoustic images in just seconds, paving the way for their use in a clinical setting for the first time and offering the potential for ...
Collaborations empower the healthcare industry to create a vast array of medical imaging copilot applications that will help enhance radiologists’ experiences and contribute to better patient outcomes ...
When radiologist Pouneh Razavi reads a patient’s mammogram, she hunts for blips in the X-ray image that could indicate breast cancer. Then, a second reader looks at the image, and the two compare ...
Abstract: Deep learning (DL) is being utilized in different clinical imaging process and has accomplished promising results. Nonetheless, incorporating DL in clinical imaging also presents significant ...
As medical imaging continues to quickly evolve, radiation protection experts gathered at the IAEA to discuss how to best keep patients safe in this changing medical landscape. Every five years there ...
Dr. James McCaffrey of Microsoft Research tackles the process of examining a set of source data to find data items that are different in some way from the majority of the source items. Data anomaly ...
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