Results 131 to 140 of about 1,753,121 (371)

Review of the application of dual‐energy CT combined with radiomics in the diagnosis and analysis of lung cancer

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Lung cancer is one of the most common malignant tumors in the world. Early detection and precise treatment are of great significance to clinical decision‐making and patient prognosis. As an emerging imaging technology, dual‐energy computed tomography (DECT) has increasingly prominent advantages in multi‐parameter and quantitative analysis in ...
Rongyu Zhang, Hao Zheng, Jie Lin, Junna Wang   +3 more
wiley   +1 more source

"Reticular" and "Areticular" Nissl Bodies in Sympathetic Neurons of a Lizard [PDF]

, 1959
Stuart W. Smith
openalex   +1 more source

Does dose calculation algorithm affect the dosimetric accuracy of synthetic CT for MR‐only radiotherapy planning in brain tumors?

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose This study compares the dosimetric accuracy of deep‐learning‐based MR synthetic CT (sCT) in brain radiotherapy between the Analytical Anisotropic Algorithm (AAA) and AcurosXB (AXB). Additionally, it proposes a novel metric to predict the dosimetric accuracy of sCT for individual post‐surgical brain cases.
Jeffrey C. F. Lui, Francis K. H. Lee, C. C. Law, James C. H. Chow   +3 more
wiley   +1 more source

The Condition of the Vasomotor Neurons in Shock [PDF]

, 1903
W. T. Porter, William C. Quinby
openalex   +1 more source

Super Neurons

IEEE Transactions on Emerging Topics in Computational Intelligence
Self-Organized Operational Neural Networks (Self-ONNs) have recently been proposed as new-generation neural network models with nonlinear learning units, i.e., the generative neurons that yield an elegant level of diversity; however, like its predecessor, conventional Convolutional Neural Networks (CNNs), they still have a common drawback: localized ...
Serkan Kiranyaz, Junaid Malik, Mehmet Yamac, Mert Duman, Ilke Adalioglu, Esin Guldogan, Turker Ince, Moncef Gabbouj   +7 more
openaire   +4 more sources

Microtubules: The neuronic system of the neurons?

, 1997
20 pages LATEX, no figures; Invited talk by D.V.N.
Mavromatos, N. E., Nanopoulos, D. V.
openaire   +2 more sources

RETRACTION: Effect of a Neural Relay on Liver Regeneration in Mice: Activation of Serotonin Release from the Gastrointestinal Tract

FEBS Open Bio, EarlyView.
RETRACTION: R. Inoue, K. Kamimura, T. Nagoya, N. Sakai, T. Yokoo, R. Goto, K. Ogawa, Y. Shinagawa‐Kobayashi, Y. Watanabe‐Mori, A. Sakamaki, S. Abe, H. Kamimura, N. Miyamura, H. Nishina, and S. Terai, “Effect of a Neural Relay on Liver Regeneration in Mice: Activation of Serotonin Release from the Gastrointestinal Tract,” FEBS Open Bio 8, no.
wiley   +1 more source

T2‐weighted imaging of rectal cancer using a 3D fast spin echo sequence with and without deep learning reconstruction: A reader study

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose To compare image quality and clinical utility of a T2‐weighted (T2W) 3‐dimensional (3D) fast spin echo (FSE) sequence using deep learning reconstruction (DLR) versus conventional reconstruction for rectal magnetic resonance imaging (MRI).
Dan Nguyen, Sarah Palmquist, Ken‐Pin Hwang, Jingfei Ma, Usama Salem, Jia Sun, Xinzeng Wang, Jong Bum Son, Randy Ernst, Peng Wei, Harmeet Kaur, Nir Stanietzky   +11 more
wiley   +1 more source

Neuroplasticity and Microglia Functions Applied in Dense Wireless Networks

Journal of Telecommunications and Information Technology, 2019
This paper presents developments in the area of brain-inspired wireless communications relied upon in dense wireless networks. Classic approaches to network design are complemented, firstly, by the neuroplasticity feature enabling to add the learning ...
Łukasz Kułacz, Adrian Kliks
doaj   +1 more source

Neuron Platonic Intrinsic Representation From Dynamics Using Contrastive Learning [PDF]

arXiv
The Platonic Representation Hypothesis suggests a universal, modality-independent reality representation behind different data modalities. Inspired by this, we view each neuron as a system and detect its multi-segment activity data under various peripheral conditions. We assume there's a time-invariant representation for the same neuron, reflecting its
arxiv