News-Medical.Net

Advancing 3D imaging, automation, and phenotypic discovery with AI-driven high-content screening

In this interview, AZoLife Sciences speaks with Boyd Butler, a microscopy and high-content screening expert at Molecular ...
IEEE

MAFS: Masked Autoencoder for Infrared-Visible Image Fusion and Semantic Segmentation

Abstract: Infrared-visible image fusion methods aim at generating fused images with good visual quality and also facilitate the performance of high-level tasks. Indeed, existing semantic-driven ...
Scientific Research Publishing

From U-Net to Swin-Unet Transformers: The Next-Generation Advances in Brain Tumor Segmentation with Deep Learning ()

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 ...
GitHub

Ammexm/Attention-Mechanisms-in-Medical-Image-Segmentation

Abstract: Medical image segmentation plays an important role in computer-aided diagnosis. ..... Attention Mechanisms in Medical Image Segmentation: A curated list of Attention Mechanisms in Medical ...
IEEE

EU-Net: Efficient Dense Skip-Connected Autoencoder for Medical Image Segmentation

Abstract: This paper introduces EU-Net, an efficient and enhanced U-Net-like architecture designed for medical image segmentation. It comprises a lightweight encoder and decoder connected through ...