Abstract: In this paper, we present UISE, a unified image segmentation framework that achieves efficient performance across various segmentation tasks, eliminating the need for multiple specialized ...

Abstract: Medical image segmentation is critical for disease diagnosis and treatment assessment. However, concerns regarding the reliability of segmentation regions persist among clinicians, mainly ...

The Dearborn Heights Police Department in Michigan announced an "optional patch" that included text in both Arabic and English. But then the department's Facebook page, in a follow-up post apparently ...

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 ...

Medical image segmentation is at the heart of modern healthcare AI, enabling crucial tasks such as disease detection, progression monitoring, and personalized treatment planning. In disciplines like ...

Top 10 origins of code area: Top 10 object types in image heap: 1.29MB java.base 493.71kB byte[] for code metadata 1.05MB svm.jar (Native Image) 409.34kB byte[] for java.lang.String ...

In recent years, semi-supervised methods have been rapidly developed for three-dimensional (3D) medical image analysis. However, previous semi-supervised methods for three-dimensional medical images ...

Abstract: Medical image segmentation has made signiffcant strides with the development of basic models. Speciffcally, models that combine CNNs with transformers can successfully extract both local and ...

The color image of the fire hole is key for the working condition identification of the aluminum electrolysis cell (AEC). However, the image of the fire hole is difficult for image segmentation due to ...