Results 111 to 120 of about 54,446 (214)

Diffusion model‐regularized implicit neural representation for computed tomography metal artifact reduction

Quantitative Biology, Volume 14, Issue 2, June 2026.
Abstract Computed tomography (CT) images are often severely corrupted by artifacts in the presence of metals. Existing supervised metal artifact reduction (MAR) approaches suffer from performance instability on known data due to their reliance on limited paired metal‐clean data, which limits their clinical applicability. Moreover, existing unsupervised
Jie Wen, Chenhe Du, Xiao Wang, Yuyao Zhang   +3 more
wiley   +1 more source

Denoising Low‐Power CEST Imaging Using a Deep Learning Approach With a Dual‐Power Feature Preparation Strategy

Magnetic Resonance in Medicine, Volume 95, Issue 3, Page 1410-1428, March 2026.
ABSTRACT Purpose: Low‐power (LP) chemical exchange saturation transfer (CEST) Z‐spectra have significantly reduced confounding effects and enhanced peak resolvability, thereby improving the observation and quantification of various CEST effects. However, LP Z‐spectra suffer greatly from reduced contrast‐to‐noise ratio (CNR).
Yashwant Kurmi, Malvika Viswanathan, Leqi Yin, You Chen, Xiaoyu Jiang, Junzhong Xu, Zhongliang Zu   +6 more
wiley   +1 more source

Image Denoising Using Multi-ModelFusion Technique

International Journal of Computing and Related Technologies
Image denoising is a fundamental challenge in the field of image processing, with the primary goal of recovering high-quality images from noisy counterparts.
Kamal Khan, Muhammad Anwar, Saifullah
doaj  

Motion Correction in High‐Resolution 3D Brain MRSI Without Water and Lipid Suppression

Magnetic Resonance in Medicine, Volume 95, Issue 3, Page 1323-1335, March 2026.
ABSTRACT Purpose To develop an effective method for correcting head motion in high‐resolution, non‐water‐suppressed MRSI. Methods MRSI scans are susceptible to subject motion due to the long data acquisition time required for sufficient spatial‐spectral encodings.
Ziwen Ke, Yibo Zhao, Rong Guo, Yudu Li, Wen Jin, Huixiang Zhuang, Yao Li, Zhi‐Pei Liang   +7 more
wiley   +1 more source

High PSNR based Image Steganography [PDF]

International Journal of Advanced Engineering Research and Science, 2019
openaire   +1 more source

Evaluating the impact of deep learning‐based image denoising on low‐dose CT for lung cancer screening

Journal of Applied Clinical Medical Physics, Volume 27, Issue 2, February 2026.
Abstract Purpose Low‐dose CT (LDCT) is increasingly being adopted as a preferred method for lung cancer screening. However, the accompanying rise in image noise necessitates robust denoising strategies. Therefore, this study compared LDCT images with their denoised counterparts using objective image quality metrics and key nodule‐related features ...
Shih‐Sheng Chen, Hsiao‐Hua Liu, Ching‐Ching Yang   +2 more
wiley   +1 more source

Explicit Compression Degradation Estimations for Low‐Sampling Single‐Pixel Imaging using Hadamard Basis

Advanced Science, Volume 13, Issue 9, 13 February 2026.
This study proposes a degradation estimation technique to explicitly describe compressive sampling for low‐sampling Hadamard single‐pixel imaging. Blur kernels in explicit degradation models are estimated by the self‐supervised learning method without labeled data and implicit priors.
Haoyu Zhang, Jie Cao, Chang Zhou, Haifeng Yao, Qun Hao   +4 more
wiley   +1 more source

GLCM and PSNR Analysis of Woven Fabric Images Made from Natural Dyes Due to Sunlight Exposure

JOIV: International Journal on Informatics Visualization
Traditional woven fabrics generally use natural dyes that come from the local area. Natural dyes are often considered low quality if exposed to sunlight.
Patrisius Batarius, Albertus Joko Santoso, Alfry Aristo Jansen Sinlae   +2 more
doaj   +1 more source

Image Fusion for Super‐Resolution Mass Spectrometry Imaging of Plant Tissue

Advanced Science, Volume 13, Issue 7, 3 February 2026.
A loss controlled residual network (LCRN) workflow is developed for super‐resolution fusion of plant mass spectrometry imaging data. LCRN uses a novel edge perceptual loss metric to preserve complex plant tissue morphology. LCRN achieves up to 20‐fold magnification while effectively combining chemical information from mass spectrometry with ...
Yuchen Zou, Shipeng Sun, Weiwei Tang, Bin Li   +3 more
wiley   +1 more source

An Effective Approach for Recognition of Crop Diseases Using Advanced Image Processing and YOLOv8

Food Science &Nutrition, Volume 14, Issue 2, February 2026.
The performance of processed images is evaluated using mean‐squared‐error and peak‐signal‐to‐noise ratio. After the processing phase, an advanced deep learning model, YOLOv8, was used for the segmentation and classification of crop diseases. Using a large dataset comprising 32 diseases to train our model, we implemented Transfer Learning using YOLOv8 ...
Muhammad Nouman Noor, Muhammad Masab, Farah Haneef, Muzammil Hussain, Mateen Yaqoob, Tehseen Mazhar, Muhammad Amir Khan, Ghadah Aldehim   +7 more
wiley   +1 more source