Unsupervised learning is a branch of machine learning that focuses on analyzing unlabeled data to uncover hidden patterns, structures, and relationships. Unlike supervised learning, which requires pre ...
Abstract: Unsupervised domain adaption (UDA), which aims to enhance the segmentation performance of deep models on unlabeled data, has recently drawn much attention. In this paper, we propose a novel ...
Abstract: Obtaining pixel-level expert annotations is expensive and labor-intensive in the medical imaging field, especially for multi-modality imaging data like MR. Most conventional cross-modality ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In recent AI-driven disease diagnosis, the success of models has depended mainly on ...
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 ...
Imaging technologies are ubiquitous in our daily lives, from smartphone cameras to medical imaging devices, helping us capture images and perceive objects. However, when faced with complex ...
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