Xiangkai Wei

ORCID: 0009-0000-4313-0014
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About
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Research Areas
  • Lung Cancer Treatments and Mutations
  • Image and Signal Denoising Methods
  • Advanced Image Processing Techniques
  • Optical Coherence Tomography Applications
  • PI3K/AKT/mTOR signaling in cancer
  • Lung Cancer Research Studies
  • Generative Adversarial Networks and Image Synthesis
  • Image Processing Techniques and Applications
  • Monoclonal and Polyclonal Antibodies Research
  • Cancer-related gene regulation
  • Ferroptosis and cancer prognosis
  • Photoacoustic and Ultrasonic Imaging
  • HER2/EGFR in Cancer Research
  • Quinazolinone synthesis and applications
  • Cancer, Lipids, and Metabolism
  • RNA modifications and cancer
  • Neural Networks and Applications
  • Cancer therapeutics and mechanisms
  • Cytokine Signaling Pathways and Interactions

First Affiliated Hospital of Henan University
2023-2024

Henan University Huaihe Hospital and Huaihe Clinical Institute
2024

Wuhan University of Science and Technology
2018-2023

In magnetic resonance imaging (MRI), several images can be obtained using different settings (e.g. T1, T2, DWI, and Flair). These have similar anatomical structures but are with contrasts, which provide a wealth of information for diagnosis. However, the under specific may not available due to limitation scanning time or corruption caused by noises. It is attractive derive missing some from MR images. this paper, we propose novel end-to-end multisetting image synthesis method. The proposed...

10.1109/jstsp.2020.3013418 article EN IEEE Journal of Selected Topics in Signal Processing 2020-07-31

Medical images from different modalities, contrast sequences, and settings can provide diverse information in clinical applications medical analysis. However, some modalities or sequences may be missing degraded due to strict timing artifacts during acquisition, leaving many unpaired data. Therefore, it is meaningful synthesize realistic with This article proposed a general multi-task method for end-to-end cross-domain synthesis segmentation network, named SSA-Net, based on cycle generative...

10.1109/tetci.2023.3296499 article EN IEEE Transactions on Emerging Topics in Computational Intelligence 2023-07-26

Optical coherence tomography (OCT) is widely used in the diagnosis of ophthalmic diseases. However, OCT affected by ubiquitous speckle noise which make it difficult to analysis retinal structures. To efficiently remove as well preserve clinical detail information contained images, we suggest train a denoise generative adversarial network (DNGAN) jointly with densely connected convolutional estimate clean images from noisy images. A generator neural (CNN) several dense connections, trained...

10.1109/cisp-bmei.2018.8633086 article EN 2021 14th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) 2018-10-01

Bladder cancer is one of the most common urological malignancies worldwide. The molecular mechanism underlying its development complex, but carcinogenesis has been proposed to occur with cell proliferation and resistance apoptosis, driven by signaling activity abundant EGFR receptor tyrosine‑protein kinase erbB‑2. In present study, T24 bladder lines EGFR‑overexpression were constructed, before multi‑target inhibitor CUDC‑101 was used investigate potential as a targeted therapeutic agent for...

10.3892/ijo.2023.5579 article EN cc-by-nc-nd International Journal of Oncology 2023-10-12

The speckle noise is an inherent coproduct of OCT imaging that a significant direct influence factor image quality, thus denoising needed. Most existing methods usually use only part the priori information image, but neglect change texture, structure and other features image. To address this, we introduce framework for by multiple CNNs based on clustering residual learning. Our proposed method not utilizes automatic feature learning ability also adapts them to depict diversity...

10.1109/cisp-bmei.2018.8633065 article EN 2021 14th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) 2018-10-01

Mutations in the epidermal growth factor receptor (EGFR) gene are common driver oncogenes non-small cell lung cancer (NSCLC). Studies have shown that afatinib is beneficial for NSCLC patients with rare EGFR mutations. However, effectiveness of tyrosine kinase inhibitors (TKIs) against G719X (G719A, G719C and G719S) mutation has not been fully established. Herein, using CRISPR method, mutant lines were constructed to assess sensitivity NSCLC. WZ3146, a novel mutation-selective inhibitor, was...

10.1038/s41598-024-73293-z article EN cc-by-nc-nd Scientific Reports 2024-10-02

The epidermal growth factor receptor (EGFR) represents an effective target for the treatment of non-small cell lung cancer. In classical EGFR mutations, tyrosine kinase inhibitors have achieved desirable clinical efficacy. However, effectiveness (TKIs) against L861Q mutation has not been fully established. this study, four lines containing were constructed by CRISPR and anti-tumour effects CUDC-101 on them investigated in vitro various chemosensitivity methods, with afatinib serving as a...

10.1016/j.crtox.2024.100194 article EN cc-by-nc-nd Current Research in Toxicology 2024-01-01
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