Breaking tunnel vision, imaging AI lifts fluorescence image restoration accuracy and speed

Recent years have witnessed great advances in applying deep learning to improve fluorescence microscopy imaging. However, enhancing the fidelity of image restoration networks and improving their ...
IEEE

UMTF-Net: An Unsupervised Multiscale Transformer Fusion Network for Hyperspectral and Multispectral Image Fusion

Abstract: Hyperspectral images (HSIs) are extensively utilized in several fields due to their abundant spectral band, particularly for tasks like ground object classification and environmental ...
The Lancet

Deep learning for H&E-based meningioma molecular classification and outcome prediction: a retrospective cohort study

To our knowledge, this study is the first to apply deep learning models that can, beyond diagnosis, identify molecular subtypes and predict outcomes in a single brain tumour entity (meningioma) using ...
IEEE

MK-UNet: Multi-Kernel Lightweight CNN for Medical Image Segmentation

Abstract: In this paper, we introduce MK-UNet, a paradigm shift towards ultra-lightweight, multi-kernel U-shaped CNNs tailored for medical image segmentation. Central to MK-UNet is the multi-kernel ...