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

Deep learning has transformed remote sensing, driving state-of-the-art results in land use and land cover classification, ...

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors ...

Aim To implement a deep learning-based segmentation algorithm to quantify reticular pseudodrusen (RPD) and drusen volumes on optical coherence tomography (OCT) and investigate their association with ...

New research from FIU shows that some visual-language AI models have become particularly susceptible to image-based hacks.

Abstract: Deep learning has achieved great successes in conventional computer vision tasks. In this paper, we exploit deep learning techniques to address the hyperspectral image classification problem ...

A three-stage pipeline progressed from slit-lamp image training to smartphone optimization and public self-capture, incorporating human-computer interface refinements and preprocessing to improve real ...

Retinal imaging and deep learning (DL) may support scalable screening, but deployment requires evidence on pooled performance. This is important because missed neovascular disease may delay treatment, ...

AI medical imaging market is projected to exceed $20B by 2035. Generative models address class imbalances in medical imaging ...

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors ...

Abstract: Wounds not only harm the physical and mental health of patients, but also introduce huge medical costs. Meanwhile, there is a shortage of physicians in some areas, and clinical examinations ...