Results 91 to 100 of about 1,639 (207)

High‐Content SRS Imaging Unveils Altered Cholesterol Metabolism in Ovarian Cancers Under CAR‐T Treatment

Advanced Science, Volume 13, Issue 23, 23 April 2026.
High‐content Stimulated Raman Scattering (SRS) Imaging reveals that ovarian cancer cells surviving Chimeric Antigen Receptor (CAR) ‐T cell challenge exhibit increased cholesterol esterification. Pharmacological inhibition of this pathway with Avasimibe significantly enhances CAR‐T induced killing of ovarian cancer cells by reducing cancer cell ...
Chinmayee V. Prabhu Dessai, Zhuoying Huang, Haonan Lin, Guangrui Ding, Hongjian He, Menna Siddiqui, Meng Zhang, Wilson Wong, Ji‐Xin Cheng   +8 more
wiley   +1 more source

3D medical volume segmentation using hybrid multiresolution statistical approaches

, 2010
This article is available through the Brunel Open Access Publishing Fund. Copyright © 2010 S AlZu’bi and A Amira.3D volume segmentation is the process of partitioning voxels into 3D regions (subvolumes) that represent meaningful physical entities which ...
Alzubi, S, Amira, A, Shadi AlZu'bi, Abbes Amira   +3 more
core   +1 more source

Hyperspectral Image Restoration with Self-supervised Learning: A Two-stage Training Approach

, 2021
Hyperspectral image (HSI) denoising is a crucial preprocessing task to improve the performance of the subsequent HSI interpretation and applications.
Chen, L, Zhou, J, Zhu, H, Qian, Y
core   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, Volume 2, Issue 2, April 2026.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Hyperspectral Imaging Combined With Image Fusion Features and Machine Learning to Discriminate Different Origins, Grades, and Shelf‐Life of Oranges

Food Safety and Health, Volume 4, Issue 2, Page 451-463, April 2026.
This study verified that it is feasible to distinguish oranges of different origins, grades and shelf lives by using hyperspectral technology. It covers spectral, image and graph technologies, as well as machine learning and deep learning models. ABSTRACT This study reports the first application of hyperspectral feature fusion technology combined with ...
Honghui Xiao, Hao Hu, Hanyi Mei, Hao Deng, Yongzhi Zhang, Jing Nie, Hao Wu, Karyne M. Rogers, Yuwei Yuan, Chunlin Li   +9 more
wiley   +1 more source

Hyperspectral Image Denoising Using Nonconvex Local Low-Rank and Sparse Separation With Spatial-Spectral Total Variation Regularization. [PDF]

IEEE Trans Geosci Remote Sens, 2022
Peng C, Liu Y, Kang K, Chen Y, Wu X, Cheng A, Kang Z, Chen C, Cheng Q.   +8 more
europepmc   +1 more source

Deep Self-Supervised Image Denoising for Joint Hyperspectral-Lidar Classification

The land cover classification is an essential task in remote sensing that assigns categories to pixels in a scene. Until now, it has been mainly solved using one single modality, which experiences limitations in complex scenes that contain different ...
Middelmann, Wolfgang, Schenkel, Fabian, Groß, Wolfgang, Gonzalez-Santiago, Jonathan   +3 more
core   +1 more source

Hyperspectral Image Denoising via Spatial-Spectral Recurrent Transformer

Hyperspectral images (HSIs) often suffer from noise arising from both intra-imaging mechanisms and environmental factors. Leveraging domain knowledge specific to HSIs, such as global spectral correlation (GSC) and non-local spatial self-similarity (NSS),
Zhou, Jun, Qian, Yuntao, Xiong, Fengchao, Lu, Jianfeng, Zhou, Jiantao, Fu, Guanyiman   +5 more
core   +1 more source

Hyperspectral image denoising

, 2020
Šiame darbe analizavome hiperspektrinius vaizdus, hiperspektrinias vaizdavimo technologijas ir triukšmo kilmę hiperspektriniuose vaizduose. Mes ištyrėme ir įgyvendinome kelis HSI triukšmo vertinimo metodus: koreliacijos koeficientų suradimo metodikas (R1 ir R2) ir tiesinės regresijos metodikas (LMLSD ir SSDC).
openaire   +1 more source

Weighted Total Variation for Hyperspectral Image Denoising Based on Hyper-Laplacian Scale Mixture Distribution

Remote Sensing
Conventional total variation (TV) regularization methods based on Laplacian or fixed-scale Hyper-Laplacian priors impose uniform sparsity penalties on gradients.
Xiaoyu Yu, Jianli Zhao, Sheng Fang, Tianheng Zhang, Liang Li, Xinyue Huang   +5 more
doaj   +1 more source