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Medical image prediction plays a very significant role in clinical decision-making and early detection and diagnosis of different diseases. However, the quality of medical images has a huge impact on the predictive model...

Abstract Quantitative analysis of fluorescence microscopy images remains a significant challenge in cytopathological assessments, as subjective interpretation and inter‐observer variability hinder reproducibility and s...

Abstract Medical images are inherently high-resolution and contain locally varying structures that are crucial for diagnosis. Efficient compression of such data must therefore preserve diagnostic fidelity while minimizin...

The article presents the developed algorithm and software for automated monitoring of strawberry plant growth using neural network technologies. The YOLO11x and YOLOx-seg models, pre-trained by transfer learning, are ada...

Abstract Skin diseases affect a considerable part of the world population, but it is not easy to diagnose these diseases on time because of the limited availability of dermatologists and the similarity of lesions. This r...

Macromolecular crystallography provides mechanistic understanding of biological processes and can be applied in drug design. Nowadays, the use of robotic systems for crystal growth and diffraction analysis is widespread ...

Event-based image processing represents an emerging research field within computer vision and is gaining increasing relevance in modern imaging technologies. In contrast to conventional frame-based approaches, neuromorph...

In conditions of rapid change, the strategic stability of agricultural enterprises and the ability to innovate are key factors in ensuring regional economic stability and food security. The purpose of the article is to s...

Abstract Lumbar spine disorders represent a significant public health concern, with accurate diagnosis relying on vertebral segmentation and quantification. Traditional methods, such as Cobb angle measurement are constra...