Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.plrev.2025.02.011 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
From multi-scale to non-local models: Comment on "Mathematical models on Alzheimer's disease and its treatment: A review" by M. Maji & S. Khajanchi.
Phys Life Rev
March 2025
Department of Mathematics, Iowa State University, Ames, IA 50011, USA.
Dual-Domain Self-Supervised Deep Learning with Graph Convolution for Low-Dose Computed Tomography Reconstruction.
J Imaging Inform Med
February 2025
School of Data Science and Artificial Intelligence, Wenzhou University of Technology, Ouhai District, Wenzhou, 325000, Zhejiang, China.
X-ray computed tomography (CT) is a commonly used imaging modality in clinical practice. Recent years have seen increasing public concern regarding the ionizing radiation from CT. Low-dose CT (LDCT) has been proven to be effective in reducing patients' radiation exposure, but it results in CT images with low signal-to-noise ratio (SNR), failing to meet the image quality required for diagnosis.
View Article and Find Full Text PDFA texture enhanced attention model for defect detection in thermal protection materials.
Sci Rep
February 2025
Department of Electronic and Electrical Engineering, Brunel University London, Uxbridge, UB8 3PH, UK.
Thermal protection materials are widely used in the aerospace field, where detecting internal defects is crucial for ensuring spacecraft structural integrity and safety in extreme temperature environments. Existing detection models struggle with these materials due to challenges like defect-background similarity, tiny size, and multi-scale characteristics. Besides, there is a lack of defect datasets in real-world scenarios.
View Article and Find Full Text PDFMetastasis lesion segmentation from bone scintigrams using encoder-decoder architecture model with multi-attention and multi-scale learning.
Quant Imaging Med Surg
January 2025
School of Computing, Mathematics and Engineering, Charles Sturt University, Albury, Australia.
Background: The limitation in spatial resolution of bone scintigraphy, combined with the vast variations in size, location, and intensity of bone metastasis (BM) lesions, poses challenges for accurate diagnosis by human experts. Deep learning-based analysis has emerged as a preferred approach for automating the identification and delineation of BM lesions. This study aims to develop a deep learning-based approach to automatically segment bone scintigrams for improving diagnostic accuracy.
View Article and Find Full Text PDFAdaptive Kernel Convolutional Stereo Matching Recurrent Network.
Sensors (Basel)
November 2024
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China.
For binocular stereo matching techniques, the most advanced method currently is using an iterative structure based on GRUs. Methods in this class have shown high performance on both high-resolution images and standard benchmarks. However, simply replacing cost aggregation with a GRU iterative method leads to the original cost volume for disparity calculation lacking non-local geometric and contextual information.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!