Annotating regions of interest in medical images, a process known as segmentation, is often one of the first steps clinical ...

MIT researchers developed an AI tool, MultiverSeg, to simplify the annotation of medical images for clinical research.

MIT researchers developed an interactive, AI-based system that enables users to rapidly annotate areas of interest in new biomedical imaging datasets, without training a machine-learning model in ...

MIT researchers have created MultiverSeg, an artificial intelligence system that accelerates the segmentation of medical ...

Xipu, University of Liverpool Joint Publication!"Can't see clearly at night? A systematic review breaks through the low-light vision dilemma" ...

ABSTRACT: Magnetic Resonance Imaging (MRI) is commonly applied to clinical diagnostics owing to its high soft-tissue contrast and lack of invasiveness. However, its sensitivity to noise, attributable ...

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 ...

Abstract: Deep learning models for medical image segmentation often struggle with task-specific characteristics, limiting their generalization to unseen tasks with new anatomies, labels, or modalities ...

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 ...