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 ...

We propose SegDINO, an efficient image segmentation framework that couples a frozen DINOv3 backbone with a lightweight MLP decoder, achieving state-of-the-art performance on both medical and natural ...

Jasmine Paolini was battling Destanee Aiava in the first round of the US Open when an Italian photographer snapped a perfect picture of her. / Amber Searls-Imagn Images Italian photographer Ray ...

Brain tumor segmentation is a vital step in diagnosis, treatment planning, and prognosis in neuro-oncology. In recent years, deep learning approaches have revolutionized this field, evolving from the ...

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 ...

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 ...

I have performed segmentation as shown in the tutorial and I want to know if its possible to get polygons out of the segmented parts in the output orthoimage. This is my input ortho image. And this is ...

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 ...