Results 21 to 30 of about 12,432,034 (314)
Advances of gold nanoclusters for bioimaging
iScience, 2022 Summary: Gold nanoclusters (AuNCs) have become a promising material for bioimaging detection because of their tunable photoluminescence, large Stokes shift, low photobleaching, and good biocompatibility.
Cheng Zhang +6 more
doaj +1 more source
Addressing fairness in artificial intelligence for medical imaging
Nature Communications, 2022 A plethora of work has shown that AI systems can systematically and unfairly be biased against certain populations in multiple scenarios. The field of medical imaging, where AI systems are beginning to be increasingly adopted, is no exception.
M. A. Ricci Lara +2 more
semanticscholar +1 more source
Speckle filtering techniques for different quality level of healthy kidney ultrasound images [PDF]
, 2019 The increasing reliance of modern medicine on diagnostic techniques such as computerized tomography, histopathology, magnetic resonance imaging, radiology and ultrasound imaging shows the importance of medical images [1].
Nazari, Ain +2 more
core +1 more source
EJNMMI Physics, 2022 Background The present study aimed to explore the boundary of acquisition time and propose an optimized acquisition time range for total-body positron emission tomography (PET)/computed tomography (CT) oncological imaging using half-dose (1.85 MBq/kg ...
Yibo He +10 more
doaj +1 more source
Diagnostic accuracy of deep learning in medical imaging: a systematic review and meta-analysis
npj Digital Medicine, 2021 Deep learning (DL) has the potential to transform medical diagnostics. However, the diagnostic accuracy of DL is uncertain. Our aim was to evaluate the diagnostic accuracy of DL algorithms to identify pathology in medical imaging. Searches were conducted
R. Aggarwal +7 more
semanticscholar +1 more source
Self-supervised learning methods and applications in medical imaging analysis: a survey [PDF]
PeerJ Computer Science, 2021 The scarcity of high-quality annotated medical imaging datasets is a major problem that collides with machine learning applications in the field of medical imaging analysis and impedes its advancement.
Saeed Shurrab, R. Duwairi
semanticscholar +1 more source
Mobile consultant: Combining total mobility with constant access [PDF]
, 2006 Minimizing the time required for a medical consultant to offer his/her expert opinion, can be viewed as a life-saving procedure. We have designed and tested an integrated system that will allow a medical consultant to freely move either within, or ...
Banitsas, KA +3 more
core +3 more sources
The organizational implications of medical imaging in the context of Malaysian hospitals [PDF]
, 2010 This research investigated the implementation and use of medical imaging in the context of Malaysian hospitals. In this report medical imaging refers to PACS, RIS/HIS and imaging modalities which are linked through a computer network.
Mohd Nor, Rohaya, Mohd Nor, Rohaya
core +1 more source
End-to-end privacy preserving deep learning on multi-institutional medical imaging
Nature Machine Intelligence, 2021 Using large, multi-national datasets for high-performance medical imaging AI systems requires innovation in privacy-preserving machine learning so models can train on sensitive data without requiring data transfer.
Georgios Kaissis +13 more
semanticscholar +1 more source
Robust, atlas-free, automatic segmentation of brain MRI in health and disease
Heliyon, 2019 Background: Brain- and lesion-volumes derived from magnetic resonance images (MRI) serve as important imaging markers of disease progression in neurodegenerative diseases and aging.
Kartiga Selvaganesan +13 more
doaj +1 more source