Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving classification and segmentation tasks.

The YOLOv8 and Swin Transformer dual-module system significantly improves structural crack detection, offering a faster and more accurate inspection method.

Medical image segmentation is a fundamental component of many clinical applications such as computer-aided diagnosis, radiotherapy planning, and preoperative planning. Its accuracy and stability ...

1 School of Science, Tianjin University of Technology and Education, Tianjin, China. 2 School of Big Data, Lvliang Vocational and Technical College, Lvliang, China. Early image segmentation was mainly ...

Abstract: Propagation-based methods have drawn increasing research attention in interactive medical image segmentation. However, existing propagation-based methods face two significant challenges: 1) ...

A research team led by Prof. WANG Huanqin at the Institute of Intelligent Machines, the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, recently proposed a semi-supervised ...

A new artificial intelligence (AI) tool could make it much easier-and cheaper-for doctors and researchers to train medical imaging software, even when only a small number of patient scans are ...

Abstract: In recent years, deep learning has been widely utilized in the fields of biomedical image segmentation and cellular image analysis. Supervised deep neural networks trained on annotated data ...

1 School of Electrical and Electronic Engineering, Wuhan Polytechnic University, Wuhan, China 2 School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, China ...

Introduction: Laryngeal high-speed video (HSV) is a widely used technique for diagnosing laryngeal diseases. Among various analytical approaches, segmentation of glottis regions has proven effective ...