Results 51 to 60 of about 19,235 (216)

PD‐1 Inhibits CD4+ TRM‐Mediated cDC1 Mobilization via Suppressing JAML in Human NSCLC

Advanced Science, EarlyView.
CD4+ tissue‐resident memory T cells (TRMs) in non‐small cell lung cancer recruit conventional type 1 dendritic cells via XCL1‐XCR1 signaling, orchestrating antitumor immunity. The costimulatory molecule JAML is essential for this process. PD‐1 blockade restores JAML expression and cDC1 mobilization, while JAML agonists synergize with anti‐PD‐1 therapy,
Zheyu Shao, Qinyuan Liu, Zhongwei Xin, Zhiyao Zhou, Mingjie Lin, Di Chen, Zhixing Hao, Yongyuan Chen, Wenxuan Wu, Shuyang Zhang, Xiaoke Chen, Xia Xu, Jinfan Li, Wei Lin, Yuhao Lu, Dang Wu, Pin Wu   +16 more
wiley   +1 more source

Clustered Multitask Nonnegative Matrix Factorization for Spectral Unmixing of Hyperspectral Data

, 2019
In this paper, the new algorithm based on clustered multitask network is proposed to solve spectral unmixing problem in hyperspectral imagery. In the proposed algorithm, the clustered network is employed.
Khoshsokhan, Sara, Rajabi, Roozbeh, Zayyani, Hadi   +2 more
core   +1 more source

Spectral mixture analysis of EELS spectrum-images [PDF]

, 2012
Recent advances in detectors and computer science have enabled the acquisition and the processing of multidimensional datasets, in particular in the field of spectral imaging.
Brun, Nathalie, Dobigeon, Nicolas
core   +3 more sources

Real‐Time In Vivo Visualization of Tumor‐Associated Macrophage Reprogramming Using a Nitric Oxide‐Activatable NIR‐II Nanoinducer

Advanced Science, EarlyView.
Reprogramming tumor‐associated macrophages is a promising therapeutic strategy for solid tumors. Here, a nitric oxide (NO)‐activatable NIR‐II fluorescence/photoacoustic nanoinducer (I/E@M2pep) that simultaneously facilitates and visualizes the repolarization of TAMs to an M1‐like phenotype is reported, thereby enhancing anti‐tumor efficacy through M1 ...
Qian Chen, Meng Li, Tuanwei Li, Chen Yang, Xiaohu Yang, Hongchao Yang, Yejun Zhang, Chunyan Li, Qiangbin Wang   +8 more
wiley   +1 more source

A New Fast Sparse Unmixing Algorithm Based on Adaptive Spectral Library Pruning and Nesterov Optimization

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
In recent years, hyperspectral sparse unmixing (HSU) has garnered extensive research and attention due to its unique characteristic of not requiring the estimation of endmembers and their number.
Kewen Qu, Fangzhou Luo, Huiyang Wang, Wenxing Bao   +3 more
doaj   +1 more source

Generalized linear mixing model accounting for endmember variability

, 2017
Endmember variability is an important factor for accurately unveiling vital information relating the pure materials and their distribution in hyperspectral images.
Bermudez, José Carlos Moreira, Borsoi, Ricardo Augusto, Imbiriba, Tales   +2 more
core   +1 more source

Estimating the number of endmembers in hyperspectral images using the normal compositional model and a hierarchical Bayesian algorithm. [PDF]

, 2010
This paper studies a semi-supervised Bayesian unmixing algorithm for hyperspectral images. This algorithm is based on the normal compositional model recently introduced by Eismann and Stein.
Dobigeon, Nicolas, Eches, Olivier, Tourneret, Jean-Yves   +2 more
core   +2 more sources

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

Advanced Intelligent Discovery, EarlyView.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu, Rujia Liu, Xinyan Zhang, Xun Chen, Shuhua Yue   +4 more
wiley   +1 more source

ASSESSING AND COMPARING THE PERFORMANCE OF ENDMEMBER EXTRACTION METHODS IN MULTIPLE CHANGE DETECTION USING HYPERSPECTRAL DATA [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019
Endmember extraction is a process to identify the hidden pure source signals from the mixture. Endmember finding has become increasingly important in hyperspectral data exploitation because endmembers can be used to specify unknown particular spectral ...
H. Jafarzadeh, M. Hasanlou
doaj   +1 more source

Spectral Unmixing of Hyperspectral Imagery Using Multilayer NMF [PDF]

IEEE Geoscience and Remote Sensing Letters, 2015
5 pages ...
Roozbeh Rajabi, Hassan Ghassemian
openaire   +2 more sources