Results 51 to 60 of about 37,104 (149)

Explainable human‐in‐the‐loop healthcare image information quality assessment and selection

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Smart healthcare applications cannot be separated from healthcare data analysis and the interactive interpretability between data and model. A human‐in‐the‐loop active learning approach is introduced to reduce the cost of healthcare data labelling by evaluating the information quality of unlabelled medical data and then screening the high ...
Yang Li, Sezai Ercisli
wiley   +1 more source

Coherence Awareness in Diffractive Neural Networks

Laser &Photonics Reviews, EarlyView.
It is demonstrated that spatial coherence significantly impacts all‐optical diffractive neural networks, unlike imaging systems. A general framework is proposed for training diffractive networks for any specified degree of spatial and temporal coherence. Coherence‐blind networks are further introduced, which are resilient to illumination changes. These
Matan Kleiner, Lior Michalei, Tomer Michalei   +2 more
wiley   +1 more source

Solving an Augmented Nonnegative Matrix Factorization Model by Modified Scaled Nonmonotone Memoryless BFGS Methods Devised Based on the Ellipsoid Vector Norm

Mathematical Methods in the Applied Sciences, EarlyView.
ABSTRACT We suggest a modified version of the nonnegative matrix factorization problem, adding penalty terms to the model with the aim of taking control of the condition number of the decomposition elements. This measure is taken to reinforce computational stability in the solution path of the relevant optimization model.
Fatemeh Dargahi, Saman Babaie‐Kafaki, Zohre Aminifard, Mohammad Hajian Berenjestanaki   +3 more
wiley   +1 more source

Deep learning framework for interpretable quality control of echocardiography video

Medical Physics, EarlyView.
Abstract Background Echocardiography (echo) has become an indispensable tool in modern cardiology, offering real‐time imaging that helps clinicians evaluate heart function and identify abnormalities. Despite these advantages, the acquisition of high‐quality echo is time‐consuming, labor‐intensive, and highly subjective.
Liwei Du, Wufeng Xue, Zhanru Qi, Zhongqing Shi, Guanjun Guo, Xin Yang, Dong Ni, Jing Yao   +7 more
wiley   +1 more source

Container applications for the development and integration of virtual imaging platforms

Medical Physics, EarlyView.
Abstract Background Virtual imaging trials (VIT) have made significant advancements through the development of realistic human anatomy models, scanner‐specific simulations, and virtual image interpretation. To promote VIT widespread adoption in the medical imaging community, it is important to develop methods that unify and facilitate the use of VITs ...
Bruno Barufaldi, Miguel A. Lago, Ehsan Abadi, Andrew D. A. Maidment   +3 more
wiley   +1 more source

Mitigating RF jamming attacks at the physical layer with machine learning

IET Communications, Volume 17, Issue 1, Page 12-28, January 2023., 2023
Abstract Wireless communication devices must be protected from malicious threats, including active jamming attacks, due to the widespread use of wireless systems throughout our every‐day lives. Jamming mitigation techniques are predominately evaluated through simulation or with hardware for very specific jamming conditions.
Marko Jacovic, Xaime Rivas Rey, Geoffrey Mainland, Kapil R. Dandekar   +3 more
wiley   +1 more source

Generalizable, sequence‐invariant deep learning image reconstruction for subspace‐constrained quantitative MRI

Magnetic Resonance in Medicine, EarlyView.
Abstract Purpose To develop a deep subspace learning network that can function across different pulse sequences. Methods A contrast‐invariant component‐by‐component (CBC) network structure was developed and compared against previously reported spatiotemporal multicomponent (MC) structure for reconstructing MR Multitasking images.
Zheyuan Hu, Zihao Chen, Tianle Cao, Hsu‐Lei Lee, Yibin Xie, Debiao Li, Anthony G. Christodoulou   +6 more
wiley   +1 more source

HR‐HAR: A hierarchical relation representation for human activity recognition based on Wi‐Fi

IET Communications, Volume 17, Issue 1, Page 29-44, January 2023., 2023
Abstract The Wi‐Fi‐based human activity recognition shows immense potential, as it is device‐free, non‐intrusive to privacy, and low‐cost. However, current learning‐based recognition methods mostly adopt the hybrid representation without distinguished contributions of features to different activities, which will be seriously affected by environment ...
Yanglin Pu, Yongqiang Jiang, Hai‐Miao Hu   +2 more
wiley   +1 more source

Learning‐based motion artifact correction in the Z‐spectral domain for chemical exchange saturation transfer MRI

Magnetic Resonance in Medicine, EarlyView.
Abstract Purpose To develop and evaluate a physics‐driven, saturation contrast‐aware, deep‐learning‐based framework for motion artifact correction in CEST MRI. Methods A neural network was designed to correct motion artifacts directly from a Z‐spectrum frequency (Ω) domain rather than an image spatial domain. Motion artifacts were simulated by modeling
Munendra Singh, Sultan Z. Mahmud, Vivek Yedavalli, Jinyuan Zhou, David Olayinka Kamson, Peter van Zijl, Hye‐Young Heo   +6 more
wiley   +1 more source

Quality‐enabled decentralized dynamic IoT platform with scalable resources integration

IET Communications, EarlyView., 2022
Abstract The Internet of Things (IoT) are standard inter connected devices aimed at join everyday object to the internet. This ecosystem include manufacturing, agriculture, smart cities, industry, as well as healthcare. The capacity of controlling and monitoring the objects of the physical world using IoT generate numerous opportunities.
Biswaranjan Bhola, Raghvendra Kumar, Preeti Rani, Rohit Sharma, Mazin Abed Mohammed, Kusum Yadav, Shoayee Dlaim Alotaibi, Lulwah M. Alkwai   +7 more
wiley   +1 more source