Results 281 to 290 of about 264,517 (319)

SAGE: Spatially Aware Gene Selection and Dual‐View Embedding Fusion for Domain Identification in Spatial Transcriptomics

Advanced Science, EarlyView.
SAGE is a unified framework for spatial domain identification in spatial transcriptomics that jointly models tissue architecture and gene programs. Topic‐driven gene selection (NMF plus classifier‐based scoring) highlights spatially informative genes, while dual‐view graph embedding fuses local expression and non‐local functional relations.
Yi He, Yunpei Xu, Liqing Ding, Hong‐Dong Li, Yaohang Li, Shaokai Wang   +5 more
wiley   +1 more source

Effects of different combinations of noise index and preset adaptive statistical iterative reconstruction Veo on the accuracy and image quality of bone mineral density measurements using fast kilovolt-switching dual-energy computed tomography: a phantom study. [PDF]

Quant Imaging Med Surg
Zhang H, Han H, Li Y, Yang Q, Yin T, Yu W.   +5 more
europepmc   +1 more source

Fast reconstruction of SMS bSSFP myocardial perfusion images using noise map estimation network (NoiseMapNet): a head-to-head comparison with parallel imaging and iterative reconstruction. [PDF]

Front Cardiovasc Med
Adam NL, Kowalik G, Tyler A, Mooiweer R, Neofytou AP, McElroy S, Kunze K, Speier P, Stäb D, Neji R, Nazir MS, Razavi R, Chiribiri A, Roujol S.   +13 more
europepmc   +1 more source

Computed tomography dose index determination in dose modulation prospectively involving the third-generation iterative reconstruction and noise index. [PDF]

J Appl Clin Med Phys
Scott AW, Alancherry ASP, Lee C, Eastman E, Zhou Y.   +4 more
europepmc   +1 more source

A comparative analysis of deep learning and hybrid iterative reconstruction algorithms with contrast-enhancement-boost post-processing on the image quality of indirect computed tomography venography of the lower extremities. [PDF]

BMC Med Imaging
Du H, Sui X, Zhao R, Wang J, Ming Y, Piao S, Wang J, Ma Z, Wang Y, Song L, Song W.   +10 more
europepmc   +1 more source

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Iterative Reconstruction

2023
An improved iterative reconstruction method to reconstruct a first image includes generating an imaging beam, receiving said imaging beam on a detector array, generating projection data based on said imaging beams received by said detector array, providing said projection data to an image reconstructor, enlarging one of a plurality of voxels and a ...
De Man, Bruno Kristiaan Bernard, Bouman, Charles A., Thibault, Jean-Baptiste, Hsieh, Jiang, Zeng, Kai, Sauer, Ken D, Yu, Zhou   +6 more
openaire   +1 more source

Iterative reconstruction algorithms

Computers in Biology and Medicine, 1976
Abstract In this paper a survey of recent results on iterative reconstruction algorithms is given. These results, many of which have not yet appeared elsewhere, are applicable to a very general formulation of the reconstruction problem based on the series expansion approach.
G T, Herman, A, Lent
openaire   +2 more sources

Adaptive iterative reconstruction

SPIE Proceedings, 2011
It is well known that, in CT reconstruction, Maximum A Posteriori (MAP) reconstruction based on a Poisson noise model can be well approximated by Penalized Weighted Least Square (PWLS) minimization based on a data dependent Gaussian noise model. We study minimization of the PWLS objective function using the Gradient Descent (GD) method, and show that ...
H. Bruder, R. Raupach, J. Sunnegardh, M. Sedlmair, K. Stierstorfer, T. Flohr   +5 more
openaire   +1 more source