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Dermoscopy is the main tool for early detection of skin cancer. Non-contact dermoscopes often suffer from a small depth of field leading to images of skin topographies with regions that are not in focus. We aim to provide an easy-to-implement focus stacking-based approach to ensure all-in-focus images from a non-contact dermoscope. Further, we aim to extract additional information about the skin topography from the image stacks. The focus stacking procedure itself is implemented in a non-contact dermoscope with an electrically adjustable focus realized by using a tunable liquid lens. We show that all-in-focus imaging is possible for non-contact dermoscopy and deliver a method to extract topographical information for dermatologists from the acquired image stacks. Our finding indicate that the approach can be valuable for non-contact dermoscopic examination as well as for the early detection of skin diseases such as cancer as it possible to derive hyperfocus images and information on the skin topography. With this, we were able to develop a software for the acquisition of the raw image data and its processing into a high resolution hyperresolution dermoscopic image. In the next steps, we plan to apply the approach in the clinical environment for skin cancer diagnostics or imaging of inflammatory skin diseases.
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http://dx.doi.org/10.1088/2057-1976/ac9847 | DOI Listing |
Phys Chem Chem Phys
September 2025
Center S3, CNR Institute of Nanoscience, via Campi 213/A, 41125 Modena, Italy.
Infrared spectroscopy is widely used to probe the structural organization of biologically relevant molecules, including peptides, proteins, and nucleic acids. The latter show significant structural diversity, and specific infrared bands provide insights into their conformational ensembles. Among DNA/RNA infrared bands, the CO stretching modes are especially useful, as they are sensitive to the distinct structural arrangements within nucleic acids.
View Article and Find Full Text PDFNeural Netw
August 2025
School of Innovation Experiment, Dalian University of Technology, Dalian, 116024, China; School of Information and Communication Engineering, Dalian Minzu University, Dalian, 116600, China. Electronic address:
Mainstream approaches to spectral reconstruction primarily focus on Convolution- and Transformer-based architectures. However, CNN methods fall short in handling long-range dependencies, whereas Transformers are constrained by computational efficiency limitations. Therefore, constructing a efficient spectral reconstruction network while ensuring the quality of reconstructed hyperspectral images (HSIs) has become a major challenge.
View Article and Find Full Text PDFAdv Exp Med Biol
August 2025
Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, Leipzig University, Leipzig, Germany.
At the level of secondary structure, circular RNAs (circRNAs) can be understood in terms of base pairing, base-pair stacking, and entropic loop contribution in the same way as linear RNAs and intermolecular RNA-RNA interactions. The folding problem of circular RNAs can thus be solved by dynamic programming algorithms in essentially the same manner. In this chapter, we review the similarities and differences between circular and linear RNAs with a focus on the software tools provided by the ViennaRNA package.
View Article and Find Full Text PDFInt J Med Inform
December 2025
Department of Allied and Public Health, School of Health, Sport and Bioscience, University of East London, London, United Kingdom; Department of Research and Innovation, Medway NHS Foundation Trust, Gillingham ME7 5NY, United Kingdom; Department of Public Health, York St John University, London, Uni
Background: Alzheimer's disease (AD) represents a significant global health challenge requiring early and accurate prediction for effective intervention. While machine learning models demonstrate promising capabilities in AD prediction, their black-box nature limits clinical adoption due to a lack of interpretability and transparency.
Objective: This study aims to develop and evaluate explainable artificial intelligence (XAI) frameworks for AD prediction using comprehensive multimodal patient data, with a focus on enhancing model interpretability through SHAP and LIME techniques.
Micromachines (Basel)
July 2025
Department of Electronic Engineering, Hanyang University, 222 Wangsimni-ro, Seoul 04763, Republic of Korea.
Oblique angle deposition (OAD) holds significant potential for diverse applications, including energy harvesting devices, optoelectronic sensors, and electronic devices, owing to the creation of unique nanostructures. These nanostructures are characterized by their porosity and nanoscale columns, which can exist in numerous forms depending on deposition conditions. As a result, the engineering of nanostructures using OAD achieves the successful modulation of optical properties such as absorption, reflection, and transmission.
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