98%
921
2 minutes
20
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11583672 | PMC |
http://dx.doi.org/10.1186/s13643-024-02699-7 | DOI Listing |
J Biomed Opt
September 2025
Leibniz University Hannover, Hannover Centre for Optical Technologies, Hannover, Germany.
Significance: Melanoma's rising incidence demands automatable high-throughput approaches for early detection such as total body scanners, integrated with computer-aided diagnosis. High-quality input data is necessary to improve diagnostic accuracy and reliability.
Aim: This work aims to develop a high-resolution optical skin imaging module and the software for acquiring and processing raw image data into high-resolution dermoscopic images using a focus stacking approach.
Med Phys
September 2025
School of Computer, Electronics and Information, Guangxi University, Nanning, China.
Background: Deformable medical image registration is a critical task in medical imaging-assisted diagnosis and treatment. In recent years, medical image registration methods based on deep learning have made significant success by leveraging prior knowledge, and the registration accuracy and computational efficiency have been greatly improved. Models based on Transformers have achieved better performance than convolutional neural network methods (ConvNet) in image registration.
View Article and Find Full Text PDFMed Phys
September 2025
Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China.
Background: Four-dimensional magnetic resonance imaging (4D-MRI) holds great promise for precise abdominal radiotherapy guidance. However, current 4D-MRI methods are limited by an inherent trade-off between spatial and temporal resolutions, resulting in compromised image quality characterized by low spatial resolution and significant motion artifacts, hindering clinical implementation. Despite recent advancements, existing methods inadequately exploit redundant frame information and struggle to restore structural details from highly undersampled acquisitions.
View Article and Find Full Text PDFMed Phys
September 2025
Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, China.
Background: Dual-energy computed tomography (DECT) enhances material differentiation by leveraging energy-dependent attenuation properties particularly for carbon ion therapy. Accurate estimation of tissue elemental composition via DECT can improve quantification of physical and biological doses.
Objective: This study proposed a novel machine-learning-based DECT (ML-DECT) method to predict the physical density and mass ratios of H, C, N, O, P, and Ca.
J Appl Clin Med Phys
September 2025
Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia, USA.
Purpose: Real‑time magnetic resonance-guided radiation therapy (MRgRT) integrates MRI with a linear accelerator (Linac) for gating and adaptive radiotherapy, which requires robust image‑quality assurance over a large field of view (FOV). Specialized phantoms capable of accommodating this extensive FOV are therefore essential. This study compares the performance of four commercial MRI phantoms on a 0.
View Article and Find Full Text PDF