Impact of deformable image registration on dose accumulation applied electrocardiograph-gated 4DCT in the heart and left ventricular myocardium during esophageal cancer radiotherapy [PDF]
Ying Tong +3 more
openalex +1 more source
This review outlines bottom‐up and biomimetic fabrication strategies of quantum dots, and highlights their emerging applications in biosensing, multimodal bioimaging, and intelligent cancer theranostics. It further discusses key translational barriers and future perspectives for advancing QD‐based nanomedicine toward clinical implementation.
Jie Ju +5 more
wiley +1 more source
Functional magnetic resonance imaging progressive deformable registration based on a cascaded convolutional neural network. [PDF]
Zhu Q +5 more
europepmc +1 more source
GAN-DIRNet: A Novel Deformable Image Registration Approach for Multimodal Histological Images [PDF]
Haiyue Li +6 more
openalex +1 more source
By engineering the molecular order and thickness of PDMS layers, we reconcile the stickiness and slipperiness during bubble transport. AFM measurements and MD simulations further reveal how these nanoscale architectures tune hydrophobic interaction FHB and friction force f.
Shishuang Zhang +7 more
wiley +1 more source
Using neural networks to extend cropped medical images for deformable registration among images with differing scan extents. [PDF]
McKenzie EM +5 more
europepmc +1 more source
ABSTRACT Layered 2D materials are considered as promising for memristive applications due to their ultimate vertical scalability compared to conventional semiconductor films and pronounced hysteresis properties. Bias‐resolved Raman and Photoluminescence mapping is used to quantify strain from phonon shifts and carrier density from the exciton‐trion ...
Vladislav Kurtash +4 more
wiley +1 more source
Deformable registration and generative modelling of aortic anatomies by auto-decoders and neural ODEs. [PDF]
Tenderini R +6 more
europepmc +1 more source
Deformable registration of chest CT images using a 3D convolutional neural network based on unsupervised learning. [PDF]
Zheng Y, Jiang S, Yang Z.
europepmc +1 more source

