This study aimed to evaluate the use of deep learning techniques to produce measured attenuation-corrected (MAC) images from non-attenuation-corrected (NAC) F-FDG PET images, focusing on head and neck imaging. A Residual Network (ResNet) was used to ...
Deep learning has shown great promise for improving medical image reconstruction, including positron emission tomography (PET). However, concerns remain about the stability and robustness of these methods, especially when trained on limited data. Thi...
This study aimed to validate the utility of commercially available vendor-neutral deep learning (DL) image enhancement software for improving the image quality of multiparametric MRI for gliomas in a multinational setting. A total of 294 patients fro...
Image super-resolution reconstructs high-resolution images from low-resolution inputs. However, current single-image super-resolution techniques often struggle to capture multi-scale information and extract high-frequency details, which compromises r...
Mass spectrometry imaging (MSI) is a label-free technique that enables the visualization of the spatial distribution of thousands of ions within biosamples. Data denoising is the computational strategy aimed at enhancing the MSI data quality, providi...
The lengthy 1 h dynamic positron emission tomography (PET) scans discomfort patients, add motion artifacts, and inflate costs, highlighting the need for tech advancements to reduce scan times. Therefore, we attempted to reconstruct multi-parametric i...
Time-of-flight (TOF) information provides more accurate location data for annihilation photons, thereby enhancing the quality of positron emission tomography (PET) reconstruction images and reducing noise. List-mode reconstruction has a significant a...
As a critical component of industrial equipment, the fault diagnosis of rolling bearings is essential for reducing unplanned downtime and improving equipment reliability. Existing methods achieve an accuracy of no more than 92% in low signal-to-noise...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Aug 10, 2025
PURPOSE: To visualize and assess hematoma growth trends by generating follow-up CT images within 24 h based on baseline CT images of spontaneous intracerebral hemorrhage (sICH) using Transformer-integrated Generative Adversarial Networks (GAN).
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jul 22, 2025
Optical Coherence Tomography (OCT) will inevitably be contaminated by speckle noise when imaging, resulting in a decrease in the visual quality of images and affecting clinical diagnosis. Existing unsupervised denoising methods often rely on complex ...
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