Accurate segmentation of medical images is essential for clinical decision-making, and deep learning techniques have shown remarkable results in this area. However, existing segmentation models that ...

Cloud-based solution advances personalized healthcare through scalable, personalized 3D solutions driven by artificial intelligence. BELFAST, Northern Ireland--(BUSINESS WIRE)--Axial3D, a leader in ...

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 ...

Artificial intelligence has the potential to improve the analysis of medical image data. For example, algorithms based on deep learning can determine the location and size of tumors. This is the ...

Nuclei segmentation in histology images is an import step for identifying cells and doing analysis for problems such as disease identification and/or progression. In this effort, we focus on the lack ...

Meta Platforms Inc. today is expanding its suite of open-source Segment Anything computer vision models with the release of SAM 3 and SAM 3D, introducing enhanced object recognition and ...

Nonetheless, data analysis of micro CT imaging is limited in sample size due to the significant effort required for segmentation [2]. Presently, segmenting individual bones is generally reliant on ...